SYSTEM FOR DETECTING PEDESTRIANS BY FUSING COLOR AND DEPTH INFORMATION

• US 20170032676A1
• Filed: 07/22/2016
• Published: 02/02/2017
• Est. Priority Date: 07/30/2015
• Status: Abandoned Application

• Current Assignee: Illinois Institute of Technology
• Original Assignee: Illinois Institute of Technology
• Inventors: MESMAKHOSROSHAHI, Maral, LOGHMAN, Maziar, KIM, Joohee
• Application Number:
  US15/216,934
• Publication Number:
  US 20170032676A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 18/251 of input or preprocessed data
• CPC Class Codes: G06T 2207/10012 Stereo images
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/30261 Obstacle
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G06V 10/803 of input or preprocessed 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
• CPC Class Codes: G06V 40/103 Static body considered as a whole, e.g. static pedestrian or occupant recognition
• CPC Class Codes: H04N 13/204 using stereoscopic image cameras stereoscopic photography G03B35/00
• CPC Class Codes: H04N 13/239 using two 2D image sensors having a relative position equal to or related to the interocular distance H04N13/243 takes precedence
• CPC Class Codes: H04N 2013/0081 Depth or disparity estimation from stereoscopic image signals

Abstract

A region of interest (ROI) generation method for stereo-based pedestrian detection systems. A vertical gradient of a clustered depth map is used to find ground plane and variable-sized bounding boxes are extracted on a boundary of the ground plane as ROIs. The ROIs are then classified into pedestrian and non-pedestrian classes. Simulation results show the algorithm outperforms the existing monocular and stereo-based methods.

Claims

1. A method of determining pedestrians in images taken by a stereo vision camera of a driver assistance system, the method comprising:

fusing depth and color information obtained from the camera to locate pedestrians.

2. The method of claim 1, further comprising reducing search space for pedestrian detection by finding ground plane from the images using depth information.

3. The method of claim 1, further comprising extracting ground plane from the images and generating variable-sized region of interests.

4. The method of claim 1, further comprising estimating a size of the pedestrians using depth information obtained from the stereo images.

5. The method of claim 4, further comprising calculating a size of the pedestrians on pixel by pixel basis using distance information extracted from the depth information.

6. The method of claim 1, further comprising:

clustering a depth map using uniform quantization;

extracting ground plane using a vertical gradient of the clustered depth map.

7. The method of claim 6, further comprising:

identifying a boundary of the ground plane; and

searching for pedestrians at the boundary using a plurality of variable-sized bounding boxes.

8. The method of claim 7, further comprising estimating a size of the pedestrians using depth values of boundary pixels.

9. The method of claim 6, further comprising:

generating several depth layers in the depth map;

clustering objects based upon a corresponding distance from the camera; and

estimating ground plane using a vertical gradient of the clustered depth map.

10. The method of claim 9, further comprising:

identifying a boundary of the ground plane; and

searching for pedestrians at the boundary using a plurality of variable-sized bounding boxes.

11. The method of claim 10, further comprising estimating a size of the pedestrians using depth values of boundary pixels.

12. The method of claim 11, further comprising extracting more than one bounding box for each of the boundary pixels.