Depth and Image Fusion for Road Obstacle Detection Using Stereo Camera

This paper is devoted to the detection of objects on a road, performed with a combination of two methods based on both the use of depth information and video analysis of data from a stereo camera. Since neither the time of the appearance of an object on the road, nor its size and shape is known in a...

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Bibliographic Details
Main Authors: Perezyabov, Oleg, Gavrilenkov, Mikhail, Afanasyev, Ilya
Format: Conference Proceeding
Language:English
Subjects:
dense point cloud
depth and image fusion
Filtering
graph segmentation
Image analysis
Image segmentation
Lighting
Point cloud compression
road obstacle detection
Roads
stereo camera
Streaming media
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Summary:This paper is devoted to the detection of objects on a road, performed with a combination of two methods based on both the use of depth information and video analysis of data from a stereo camera. Since neither the time of the appearance of an object on the road, nor its size and shape is known in advance, ML/DL-based approaches are not applicable. The task becomes more complicated due to variations in artificial illumination, inhomogeneous road surface texture, and unknown character and features of the object. To solve this problem we developed the depth and image fusion method that complements a search of small contrast objects by RGB-based method, and obstacle detection by stereo image-based approach with SLIC superpixel segmentation. We conducted experiments with static and low speed obstacles in an underground parking lot and demonstrated the successful work of the developed technique for detecting and even tracking small objects, which can be parking infrastructure objects, things left on the road, wheels, dropped boxes, etc.\
ISSN:2305-7254
2343-0737
DOI:10.23919/FRUCT54823.2022.9770927