Method and apparatus for an adaptive threshold based object detection

• US 9,177,214 B1
• Filed: 04/10/2014
• Issued: 11/03/2015
• Est. Priority Date: 04/10/2014
• Status: Active Grant

• Current Assignee: Conduent Business Services, LLC (Conduent, Inc.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Paul, Peter, Artan, Yusuf O.
• Primary Examiner(s): AZARIAN, SEYED H
• Application Number:
  US14/249,981
• Publication Number:
  US 20150294168A1
• Time in Patent Office: 572 Days
• Field of Search: 382/10, 382103-107, 382/155, 382/162, 382/165, 382/168, 382/173, 382/181, 382/199, 382/203, 382/209, 382/232, 382/254, 382/274, 382/276, 382286-291, 382/305, 382/312, 348/148, 348/149, 705/417, 296/76
• US Class Current: 1/1
• CPC Class Codes: G06F 18/214 Generating training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G06F 18/2433 Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 20/593 Recognising seat occupancy
• CPC Class Codes: H04N 23/21 from near infrared [NIR] radiation
• CPC Class Codes: H04N 23/611 where the recognised objects include parts of the human body
• CPC Class Codes: H04N 5/33 Transforming infrared radiation cameras or camera modules for generating image signals from infrared radiation H04N23/20; circuitry of SSIS for transforming infrared radiation into image signals H04N25/20

Abstract

A method, non-transitory computer readable medium, and apparatus for detecting an object in an image are disclosed. For example, the method receives the image, calculates a score for each one of a plurality of locations in the image, performs a box plot of the score of the each one of the plurality of locations of the image, identifies an outlier score that falls outside of the box plot, determines that a distance ratio of the outlier score is less than a predefined distance ratio and detects the object in a location of the plurality of locations of the image corresponding to the outlier score.

Claims

1. A method for detecting an object in an image, comprising:

receiving, by a processor, the image;

calculating, by the processor, a score for each one of a plurality of locations in the image;

performing, by the processor, a box plot of the score of the each one of the plurality of locations of the image;

identifying, by the processor, an outlier score that falls outside of the box plot;

determining, by the processor, that a distance ratio of the outlier score is less than a predefined distance ratio, wherein the distance ratio is a ratio that is based upon a comparison of a first distance of a second highest score and a second distance of the outlier score; and

detecting, by the processor, the object in a location of the plurality of locations of the image corresponding to the outlier score.

2. The method of claim 1, wherein the image is a near infrared (NIR) image of a vehicle.

3. The method of claim 1, wherein the object is a person and the image is analyzed to determine a total number of people in a vehicle for compliance with a high occupancy vehicle lane or a high occupancy tolling lane.

4. The method of claim 1, wherein the predefined distance ratio is based upon a plurality of training data.

5. The method of claim 1, wherein the first distance is measured from a median value of the box plot to the second highest score and the second distance is measured from the median value to the outlier score.

6. The method of claim 1, wherein the calculating is performed in accordance with a function based upon one or more landmark points and a mixture of parts of the image.

7. The method of claim 6, wherein the function is defined by an equation comprising:

8. A non-transitory computer-readable medium storing a plurality of instructions, which when executed by a processor, cause the processor to perform operations for detecting an object in an image, the operations comprising:

receiving the image;

calculating a score for each one of a plurality of locations in the image;

performing a box plot of the score of the each one of the plurality of locations of the image;

identifying an outlier score that falls outside of the box plot;

determining that a distance ratio of the outlier score is less than a predefined distance ratio, wherein the distance ratio is a ratio that is based upon a comparison of a first distance of a second highest score and a second distance of the outlier score; and

detecting the object in a location of the plurality of locations of the image corresponding to the outlier score.

9. The non-transitory computer-readable medium of claim 8, wherein the image is a near infrared (NIR) image of a vehicle.

10. The non-transitory computer-readable medium of claim 8, wherein the object is a person and the image is analyzed to determine a total number of people in a vehicle for compliance with a high occupancy vehicle lane or a high occupancy tolling lane.

11. The non-transitory computer-readable medium of claim 8, wherein the predefined distance ratio is based upon a plurality of training data.

12. The non-transitory computer-readable medium of claim 8, wherein the first distance is measured from a median value of the box plot to the second highest score and the second distance is measured from the median value to the outlier score.

13. The non-transitory computer-readable medium of claim 8, wherein the calculating is performed in accordance with a function based upon one or more landmark points and a mixture of parts of the image.

14. The non-transitory computer-readable medium of claim 13, wherein the function is defined by an equation comprising:

S(I,L,m)=App_m(I,L)+Shape_m(L)+α

^m,

15. A method for detecting an object in an image, comprising:

analyzing, by a processor, a plurality of training images having a known object to calculate a predefined distance ratio;

receiving, by the processor, the image, wherein the image is of a vehicle;

calculating, by the processor, a score for each one of a plurality of locations in the image, wherein the scoring is performed in accordance with a function based upon one or more landmark points and a mixture of parts of the image;

performing, by the processor, a box plot of the score of the each one of the plurality of locations of the image, the box plot comprising a lowest score, a 25^th percentile, a median, a 75^th percentile and a second highest score;

identifying, by the processor, an outlier score that falls outside of the box plot;

determining, by the processor, that a distance ratio of the outlier score is less than the predefined distance ratio;

detecting, by the processor, the object in a location of the plurality of locations of the image corresponding to the outlier score, wherein the object is a person; and

calculating, by the processor, a total number of objects in the image to determine if the vehicle is in violation of a total number of passengers requirement for a high occupancy vehicle lane.

16. The method of claim 15, wherein the image is a near infrared (NIR) image.

17. The method of claim 15, wherein the image is captured when the vehicle enters the high occupancy vehicle lane.

18. The method of claim 15, wherein the function is defined by an equation comprising: