Vulnerable road user protection system

• US 8,594,370 B2
• Filed: 07/26/2005
• Issued: 11/26/2013
• Est. Priority Date: 07/26/2004
• Status: Expired due to Fees

• Current Assignee: Joyson Safety Systems Acquisition, LLC (Ningbo Junsheng Investment Group Co., Ltd.)
• Original Assignee: Automotive Systems Laboratory, Incorporated (Ningbo Junsheng Investment Group Co., Ltd.)
• Inventors: Schamp, Gregory G., Davies, Owen A., Demro, James C.
• Primary Examiner(s): Bella, Matthew
• Assistant Examiner(s): BROOKS, JULIAN D
• Application Number:
  US11/658,758
• Publication Number:
  US 20090010495A1
• Time in Patent Office: 3,045 Days
• Field of Search: 382/103, 382/104, 382/106, 382/170, 382/168, 382/173, 382/224, 382/225, 701/301, 340/901, 340/435, 340/436, 340/425.5
• US Class Current: 382/103
• CPC Class Codes: B60R 21/0134 responsive to imminent contact with an obstacle , e.g. using radar systems
• CPC Class Codes: B60R 21/34 Protecting non-occupants of a vehicle, e.g. pedestrians B60R19/02 takes precedence
• CPC Class Codes: G06F 18/254 of classification results, e.g. of results related to same input data
• CPC Class Codes: G06V 10/809 of classification results, e.g. where the classifiers operate on the same input data
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads

Abstract

A range map of a visual scene generated by a stereo vision and associate image processing system, and is filtered to remove objects beyond a region of interest and for which a collision is not possible, and to remove an associated road surface. Objects clustered in range bins are separated by segmentation. A composite range map is generated using principale components analysis and processed with a connected-components sieve filter. Objects are identified using one or more of a harmonic profile and other features using an object recognition processor using a combination of inclusive, exclusive and harmonic networks to generate a classification metric.

Claims

1. A method of processing an image of a visual scene, comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram accounts for every pixel of said at least one image, said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. associating each element of said range map counted by said element of said vector with at least one of a corresponding pixel of said plurality of pixels;

e. operating on said range histogram; and

f. operating on at least one of said at least one of said corresponding pixel of said plurality of pixels associated with said element of said range map responsive to the operation of operating on said range histogram.

2. A method of processing an image of a visual scene as recited in claim 1, wherein said at least one image of said visual scene comprises at least one pair of stereo images of said visual scene, and the operation of acquiring or determining said range map comprises determining said range map from said at least one pair of stereo images of said visual scene.

3. A method of processing an image of a visual scene, comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. associating each element of said range map counted by said element of said vector with at least one of a corresponding pixel of said plurality of pixels or said range map;

e. operating on said range histogram; and

f. operating on at least one of said at least one of said corresponding pixel of said plurality of pixels or said range map associated with said element of said range map responsive to the operation of operating on said range histogram;

g. further comprising decreasing a resolution of said range map prior to calculating said range histogram by reducing a digital bit resolution of said range map prior to calculating said range histogram, so as to provide for smoothing said range map prior to calculating said range histogram.

4. A method of processing an image of a visual scene, comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. associating each element of said range map counted by said element of said vector with at least one of a corresponding pixel of said plurality of pixels or said range map;

e. operating on said range histogram; and

f. operating on at least one of said at least one of said corresponding pixel of said plurality of pixels or said range map associated with said element of said range map responsive to the operation of operating on said range histogram, wherein the operation of operating on said range histogram comprises searching said range histogram for at least one object in said visual scene responsive to a corresponding at least one cluster of elements of said range histogram, and the operation of operating on said at least one of said at least one of said corresponding pixel of said plurality of pixels or said range map associated with said element of said range map responsive to the operation of operating on said range histogram comprises nulling or ignoring each pixel of said plurality of pixels not associated with said at least one object and converting each other pixel of said plurality of pixels associated with said at least one object to a uniform value indicative of an active pixel so as to form a binary segmentation image of an entirety of said at least one image or said range map.

5. A method of processing an image of a visual scene as recited in claim 4, further comprising filling at least one hole within at least one boundary of said binary segmentation image, wherein each pixel associated with said at least one hole is converted to said uniform value indicative of said active pixel.

6. A method of processing an image of a visual scene as recited in claim 4, further comprising using an erosion filter to smooth at least one boundary of said binary segmentation image by nulling or ignoring one or more outer layers of pixels associated with said at least one boundary.

7. A method of processing an image of a visual scene, comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. associating each element of said range map counted by said element of said vector with at least one of a corresponding pixel of said plurality of pixels or said range map;

e. operating on said range histogram; and

f. operating on at least one of said at least one of said corresponding pixel of said plurality of pixels or said range map associated with said element of said range map responsive to the operation of operating on said range histogram;

g. further comprising generating a list that for each said element of said vector provides a location for each corresponding element of said range map contributing to said count of said elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value so as to facilitate the operation of operating on said at least one of said at least one of said corresponding pixel of said plurality of pixels or said range map associated with said element of said range map responsive to the operation of operating on said range histogram.

8. A method of processing an image of a visual scene as recited in claim 7, further comprising isolating relatively laterally-separated detached objects from said plurality of pixels or from said range map responsive to said list that for each said element of said vector provides said location for each said corresponding element of said range map contributing to said count of said elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value.

9. A method of processing an image of a visual scene comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. associating each element of said range map counted by said element of said vector with at least one of a corresponding pixel of said plurality of pixels or said range map;

e. operating on said range histogram; and

f. operating on at least one of said at least one of said corresponding pixel of said plurality of pixels or said range map associated with said element of said range map responsive to the operation of operating on said range histogram, wherein the operation of operating on said range histogram comprises searching said range histogram for at least one object in said visual scene responsive to a corresponding at least one cluster of elements of said range histogram, and the operation of operating on said at least one of said at least one of said corresponding pixel of said plurality of pixels or said range map associated with said element of said range map responsive to the operation of operating on said range histogram comprises nulling or ignoring each pixel of said plurality of pixels not associated with said at least one object and converting each other pixel of said plurality of pixels associated with said at least one object to a uniform value indicative of an active pixel so as to form a binary segmentation image of said at least one object; and

g. iteratively isolating laterally-spaced attached objects in said visual scene from one another in said binary segmentation image of said at least one object by searching for a best-fit rectangle in a subset of said binary segmentation image of said at least one object, having an aspect ratio associated with a vulnerable road user (VRU).

10. A method of processing an image of a visual scene as recited in claim 9, wherein the operation of searching for said best-fit rectangle having an aspect ratio associated with said vulnerable road user (VRU) comprises:

a. finding a first best fit rectangle of said binary segmentation image of said at least one object;

b. dividing said first best fit rectangle into a plurality of portions;

c. beginning at a first corner of said first best fit rectangle, finding a second best fit rectangle of a corresponding subsection of said binary segmentation image within said first best fit rectangle, wherein said corresponding subsection is bounded by one of said plurality of portions;

d. determining if said second best fit rectangle does not classify as a prospective vulnerable road user (VRU), then repeating step c for a different portion of said first best fit rectangle, or beginning at a different corner of said first best fit rectangle; and

e. otherwise, if said second best fit rectangle classifies as said prospective vulnerable road user (VRU), then subsequently processing said corresponding subsection of said binary segmentation image so as to provide for either identifying or responding to said at least one object in said visual scene.

11. A method of processing an image of a visual scene as recited in claim 10, further comprising processing a remaining portion of said first best fit rectangle in accordance with steps a-e of claim 10, excluding said corresponding subsection of said binary segmentation image corresponding to second best fit rectangle.

12. A method of processing an image of a visual scene, comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. associating each element of said range map counted by said element of said vector with at least one of a corresponding pixel of said plurality of pixels or said range map;

e. operating on said range histogram; and

f. operating on at least one of said at least one of said corresponding pixel of said plurality of pixels or said range map associated with said element of said range map responsive to the operation of operating on said range histogram so as to provide for locating at least one object within said at least one image or within said range map;

g. extracting at least one profile of at least one object from an associated boundary thereof within said at least one image or said range map, or a binary segmentation image thereof;

h. determining a corresponding center of said at least one profile;

i. determining a measurement vector comprising a plurality of distances from said corresponding center to said at least one profile at a plurality of angles relative to and through said corresponding center, wherein said plurality of angles is in excess of four;

j. comparing said measurement vector with at least one stored vector representative of at least one type of reference object; and

k. determining whether or not said at least one object corresponds to at least one said reference object responsive to the operation of comparing said measurement vector with said at least one stored vector.

13. A method of processing an image of a visual scene as recited in claim 12, wherein the operation of extracting said at least one profile of said at least one object comprises:

a. extracting a first profile of a closest object in said at least one image or said at least one image responsive thereto, responsive to at least one of said range map or said range histogram;

b. processing said first profile in accordance with steps a-e of claim 12;

c. extracting a subsequent profile of a relatively farther object in said at least one image or said at least one image responsive thereto, responsive to at least one of said range map or said range histogram; and

d. processing said subsequent profile in accordance with steps a-e of claim 12.

14. A method of processing an image of a visual scene as recited in claim 13, repeating steps c and d of claim 13 one or more times for one or more yet farther objects.

15. A method of processing an image of a visual scene as recited in claim 12, wherein the operation of determining said corresponding center of said at least one profile comprises determining a corresponding center of mass of said at least one profile.

16. A method of processing an image of a visual scene as recited in claim 12, wherein each distance of said plurality of distances is determined by first radially searching radially outwards along a search direction from said corresponding center until reaching a point on said at least one profile, and then calculating a corresponding distance of said plurality of distances, from said corresponding center to said point on said at least one profile.

17. A method of processing an image of a visual scene as recited in claim 16, wherein the operation of searching radially outwards from said corresponding center until reaching said point on said at least one profile comprises continuing to search along said search direction until finding an inactive pixel located adjacent to said point on said at least one profile.

18. A method of processing an image of a visual scene as recited in claim 12, wherein said plurality of angles are substantially equally distributed over a span of 360 degrees.

19. A method of processing an image of a visual scene as recited in claim 12, further comprising filtering said measurement vector with a central moving average filter prior to the operation of comparing said measurement vector with said at least one stored vector.

20. A method of processing an image of a visual scene as recited in claim 12, further comprising deriving said at least one stored vector from a plurality of associated measurement vectors from a corresponding plurality of different images of a corresponding said at least one said reference object.

21. A method of processing an image of a visual scene as recited in claim 12, wherein said at least one stored vector is derived as a median value of a plurality of measurement vectors from a plurality of different images of said corresponding said at least one said reference object.

22. A method of processing an image of a visual scene, comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. associating each element of said range map counted by said element of said vector with at least one of a corresponding pixel of said plurality of pixels or said map;

e. operating on said range histogram; and

f. operating on at least one of said at least one of said corresponding pixel of said plurality of pixels or said range map associated with said element of said range map responsive to the operation of operating on said range histogram so as to provide for locating at least one object within said at least one image or within said range map;

g. extracting at least one profile of at least one object from an associated boundary thereof within said at least one image or said range map, or a binary segmentation image thereof;

h. determining a corresponding center of said at least one profile;

i. determining a measurement vector comprising a plurality of distances from said corresponding center to said at least one profile at a plurality of angles relative to and through said corresponding center, wherein each distance of said of plurality of distances is determined by first radially searching radially outwards along a search direction from said corresponding center until reaching a point on said at least one profile, and then calculating a corresponding distance of said plurality of distances, from said corresponding center to said point on said at least one profile;

j. comparing said measurement vector with at least one stored vector representative of at least one type of reference object; and

k. determining whether or not said at least one object corresponds to at least one said reference object responsive to the operation of comparing said measurement vector with said at least one stored vector;

l. further comprising limiting the search along said search direction to a boundary of a best fit rectangle within said at least one image or said at least one image responsive thereto.

23. A method of processing an image of a visual scene,

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels:

b. acquiring or determining range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map for which, said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. associating each element of said range map counted by said element said vector with at least one of a corresponding pixel of said plurality of pixels or said range map;

e. operating on said range histogram; and

f. operating on at least one of said at least one of said corresponding pixel of said plurality of pixels or said range map associated with said element of said range map responsive to the operation of operating on said range histogram so as to provide for locating at least one object within said at least one image or within said range map;

g. extracting at least one profile of at least one object from an associated boundary thereof within said at least one image or said range map, or a binary segmentation image thereof;

h. determining a corresponding center of said at least one profile;

i. determining a measurement vector comprising a plurality of distances from said corresponding center to said at least one profile at a plurality of angles relative to and through said corresponding center;

j. comparing said measurement vector with at least one stored vector representative of at least one type of reference object; and

k. determining whether or not said at least one object corresponds to at least one said reference object responsive to the operation of comparing said measurement vector with said at least one stored vector;

l. further comprising deriving said at least one stored vector from a plurality of associated measurement vectors from a corresponding plurality of different images of a corresponding said at least one said reference object, wherein the operation of deriving said at least one stored vector further comprises filtering the data from said plurality of associated measurement vectors with a central moving average filter prior to storing said at least one stored vector.

24. A method of processing an image of a visual scene as recited in claim 23, wherein a length of said central moving average filter is dependent upon a type of said corresponding said at least one said reference object.

25. A method of processing an image of a visual scene as recited in claim 24, further comprising filtering said measurement vector with said central moving average filter prior to the operation of comparing said measurement vector with said at least one stored vector, wherein said length of said central moving average filter is the same for both said measurement vector and said at least one stored vector.

26. A method of processing an image of a visual scene as recited in claim 25, wherein said at least one stored vector comprises a plurality of stored vectors for a corresponding plurality of reference objects of said at least one said reference object of a variety of object classes.

27. A method of processing an image of a visual scene as recited in claim 25, wherein said length of said central moving average filter is configured so as to substantially maximize a count of intra-class measurement or stored vectors corresponding to said corresponding said at least one said reference object at different ranges that are relatively strongly cross-correlated with one another.

28. A method of processing an image of a visual scene as recited in claim 27, wherein said corresponding said at least one said reference object is selected from the group consisting of a pedal cyclist, a standing pedestrian, a walking pedestrian in full stride and a walking pedestrian in mid stride.

29. A method of processing an image of a visual scene as recited in claim 27, wherein said corresponding said at least one said reference object is selected from the group consisting of a vehicle, a dog and a trash can.

30. A method of processing an image of a visual scene, comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram accounts for every pixel of said at least one image, said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map, for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. forming at least one cluster of a plurality of associated range bins of said range histogram corresponding to at least one corresponding object in said visual scene; and

e. generating a response responsive to said at least one cluster.

31. A method of processing an image of a visual scene as recited in claim 30, wherein the operation of generating said response responsive to said at least one cluster comprises separating and isolating said at least one corresponding object in said visual scene from at least one other object in said visual scene responsive to range information associated with said at least one cluster.

32. A method of processing an image of a visual scene as recited in claim 31, wherein the operation of separating and isolating said at least one corresponding object in said visual scene from said at least one other object in said visual scene is responsive to a range spread of said at least one cluster, and said range spread of said at least one cluster is responsive to a difference between maximum and minimum ranges associated with said at least one cluster.

33. A method of processing an image of a visual scene as recited in claim 31, wherein the operation of separating and isolating said at least one corresponding object in said visual scene from said at least one other object in said visual scene is responsive to a corresponding at least one median range of a corresponding said at least one cluster.

34. A method of processing an image of a visual scene as recited in claim 30, further comprising forming a preliminary threat assessment of at least one object in said visual scene associated with said at least one cluster responsive to a median range of said at least one cluster, a count of pixels in said at least one cluster, and a range spread of said at least one cluster, wherein said range spread of said at least one cluster is responsive to a difference between maximum and minimum ranges associated with said at least one cluster.

35. A method of processing an image of a visual scene as recited in claim 30, further comprising classifying at least one object in said visual scene associated with said at least one cluster responsive to a range spread of said at least one cluster, wherein said range spread of said at least one cluster is responsive to a difference between maximum and minimum ranges associated with said at least one cluster.

36. A method of processing an image of a visual scene as recited in claim 35, wherein if said range spread is greater than a threshold, then said at least one object associated with said at least one cluster is classified as likely not a vulnerable road user (VRU).

37. A method of processing an image of a visual scene as recited in claim 35, further comprising classifying said at least one object in said visual scene associated with said at least one cluster responsive to a number of pixels in said at least one cluster.

38. A method of processing an image of a visual scene as recited in claim 30, wherein said at least one image of said visual scene comprises at least one pair of stereo images of said visual scene, and the operation of acquiring or determining said range map comprises determining said range map from said at least one pair of stereo images of said visual scene.

39. A method of processing an image of a visual scene, comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating range histogram from said range map, wherein said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map, for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. forming at least one cluster of a plurality of associated range bins of said range histogram corresponding to at least one corresponding object in said visual scene; and

e. generating a response responsive to said at least one cluster, wherein the operation of generating said response responsive to said at least one cluster comprises separating and isolating said at least one corresponding object in said visual scene from at least one other object in said visual scene responsive to range information associated with said at least one cluster, wherein the operation of separating and isolating said at least one corresponding object in said visual scene from said at least one other object in said visual scene is responsive to a composite range map generated from a plurality of sequential images of said visual scene.

40. A method of processing an image of a visual scene, comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map, for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. forming at least one cluster of a plurality associated range bins of said range histogram corresponding to least one corresponding object in said visual scene; and

;

e. generating a response responsive to said at least one cluster, wherein the operation of generating said response responsive to said at least one cluster cormprises separating and isolating said at least one corresponding object in said visual scene from at least one other object in said visual scene responsive to range information associated with said at least one cluster, wherein the operation of separating and isolating said at least one corresponding object in said visual scene from said at least one other object in said visual scene is responsive to a range spread of said at least one cluster, and said range spread of said at least one cluster is responsive to a difference between maximum and minimum ranges associated with said at least one cluster;

further comprising;

f. generating a list that for each said element of said vector provides a location for each corresponding element of said range map contributing to said count of said elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value so as to provide for isolating objects in said range map that have negligible differential range with respect to one another; and

g. processing said at least one pixel of said range map with a connected-components sieve filter,

h. wherein said connected-components sieve filter is adapted to locate at least one cluster of pixels or elements within said range map such that at least one isolated portion of said at least one cluster contains at least one pixel or element of said pixels or elements that is connected to at least one other pixel or element of said pixels or elements either along a same one of a first plurality of rows said range map, a same one of a second plurality of columns of said range map, or diagonally along both said same one of said first plurality of rows of said range map and said same one of said second pluralities of columns of said range map.

41. A method of processing an image of a visual scenes, comprising:

a. acquiring at least one image of a visual scene, wherein said at least one image comprises a plurality of pixels;

b. acquiring or determining a range map comprising at least one distance value associated with at least one pixel of said plurality of pixels, wherein said at least one distance value comprises a measure of distance relative to an associated at least one camera used to acquire said at least one image;

c. calculating a range histogram from said range map, wherein said range histogram comprises a vector, each element of said vector is associated with a different corresponding range of values of said at least one distance value, and each said element of said vector comprises a count of elements of said range map, for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value;

d. forming at least one cluster of a plurality of associated range bins of said range histogram corresponding to least one corresponding object in said visual scene; and

;

e. generating a response responsive to said at least one cluster;

further comprising;

f. decreasing a resolution of said range map prior to calculating said range histogram; and

g. generating a list that for each said element of said vector provides a location for each corresponding element of said range map contributing to said count of said elements of said range map for which said at least one distance value of said range map is within said corresponding range of values of said at least one distance value so as to provide for isolating objects in said range map that have negligible differential range with respect to one another.