PARTIALLY OCCLUDED OBJECT DETECTION USING CONTEXT AND DEPTH ORDERING

• US 20170220874A1
• Filed: 02/03/2016
• Published: 08/03/2017
• Est. Priority Date: 02/03/2016
• Status: Active Grant

• Current Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Original Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Inventors: AYVACI, Alper, HEISELE, Bernd, ZHENG, Jingjing
• Granted Patent: US 9,805,274 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06T 2207/20112 Image segmentation details
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes
• CPC Class Codes: G06V 10/42 Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
• CPC Class Codes: G06V 10/44 Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
• CPC Class Codes: G06V 10/75 Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands

Abstract

A system and method for verifying detection of partially occluded objects (e.g., pedestrians) in the vicinity of a vehicle. An image input device captures an image and/or video of surroundings. An object detector detects partially occluded pedestrians and other objects in received image information. The detection of a partially occluded pedestrian is verified when a detection window of the partially occluded pedestrian overlaps with a detection window of an occluding object, and the occluding object window is closer to the image input device than the partially occluded object window. Optionally, a range-finding sensor, such as a LIDAR device, determines a range to objects located in the direction of the partially occluded object. The detection of the partially occluded object is verified when the range of one of the other objects located in the direction of the partially occluded object is less than that of the partially occluded object.

Claims

1. A method for verifying detection of a first object partially occluded by a second object relative to a vehicle, the method comprising:

receiving image information via an image input device;

determining a first detection window bounding a first image in the image information corresponding to the first object;

determining a second detection window bounding a second image in the image information corresponding to the second object;

determining whether the first window and the second window overlap;

determining a first distance to the first detection window and a second distance to the second detection window;

comparing the first distance to the second distance, and

if the first distance is greater than the second distance, verifying that the first object is partially occluded by the second object.

2. The method of claim 1, wherein verifying that the first object is partially occluded by the second object further includes:

receiving an input from a depth sensor, the depth sensor input corresponding to a measured distance between the depth sensor and the second object;

comparing the first distance to the measured distance; and

verifying that the first distance is greater than the measured distance.

3. The method of claim 1, wherein the first object is a human.

4. The method of claim 1, wherein the first object is selected from a group consisting of a human, a bicycle, a motorcycle, and an animal.

5. The method of claim 1, wherein the image input device is a camera.

6. The method of claim 5, wherein the camera is mounted on the vehicle.

7. The method of claim 1, wherein determining whether the first window and the second window overlap includes:

determining whether the first image is a partial image.

8. The method of claim 7, wherein the first image is a human, and wherein determining whether the first image is a partial image includes:

applying human recognition to at least a portion of the first image.

9. The method of claim 2, wherein the depth sensor is selected from a group consisting of a LIDAR device, a RADAR device, and a stereo camera system.

10. A method for verifying detection of a first object partially occluded by a second object relative to a vehicle, the method comprising:

receiving image information via an image input device;

determining a first detection window bounding a first image in the image information corresponding to the first object;

determining a second detection window bounding a second image in the image information corresponding to the second object;

determining whether the first window and the second window overlap;

determining a first distance to the first detection window;

receiving an input from a depth sensor, the depth sensor input corresponding to a measured distance between the depth sensor and the second object;

comparing the first distance to the measured distance; and

if the first distance is greater than the measured distance, verifying that the first object is partially occluded by the second object.

11. A system for verifying detection of a first object partially occluded by a second object relative to a vehicle, the system comprising:

an image input device for receiving image information;

an object detector to determine a first detection window bounding a first image in the image information corresponding to the first object, and a second detection window bounding a second image in the image information corresponding to the second object; and

a processor operatively connected for computer communication to the image input device and the object detector, the processor being configured to;

determine whether the first detection window and the second detection window overlap;

if the first and second detection windows overlap, determine a first distance to the first object and determine a second distance to the second object; and

if the first distance is greater than the second distance, verify that the first object is partially occluded.

12. The system of claim 11, wherein the processor being configured to determine a first distance to the first object and determine a second distance to the second object includes:

determining a first distance to the first object using the received image information and location information for the first detection window.

13. The system of claim 12, wherein the processor being configured to determine a first distance to the first object and determine a second distance to the second object includes:

determining a second distance to the second object using the received image information and location information for the second detection window.

14. The system of claim 12, further comprising:

a depth sensor;

wherein the processor being configured to determine a first distance to the first object and determine a second distance to the second object includes;

receiving a depth sensor input corresponding to the distance between the depth sensor and the second object as the second distance.

15. The system of claim 11, wherein the first object is a human.

16. The system of claim 11, wherein the image input device is a camera.

17. The system of claim 16, wherein the camera is mounted on the vehicle.

18. The system of claim 11, wherein determining whether the first window and the second window overlap includes:

determining whether the first image is a partial image.

19. The system of claim 18, wherein the first image is a human, and wherein determining whether the first image is a partial image includes:

applying human recognition to at least a portion of the first image.

20. The system of claim 14, wherein the depth sensor is selected from a group consisting of a LIDAR device, a RADAR device, and a stereo camera system.