Title :
Detection and Segmentation of Occluded Vehicles Based on Skeleton Features
Author :
Chunyu Chen ; Shihui Liu
Author_Institution :
Dept. Inf. & Commun. Eng., Harbin Eng. Univ., Harbin, China
Abstract :
Vehicle occlusion is an important problem for vehicle detection even in the high-definition camera. The difficulty is to obtain individual vehicle from one blob when some vehicles merged together in the blob in the foreground mask. We present a method that can detect the number of occluded vehicles in one blob and the segmentation points based on the effective skeleton nodes, and then segment occluded vehicles in one blob associated with concave spots. Experiments are performed on traffic video sequences captured at two different locations, and the results appear to have good accuracy.
Keywords :
feature extraction; hidden feature removal; image segmentation; image sequences; object detection; road traffic; traffic engineering computing; video signal processing; blob; concave spot; foreground mask; high-definition camera; occluded vehicle detection; occluded vehicle segmentation; segmentation point; skeleton feature; traffic video sequence; vehicle occlusion; Cameras; Computers; Feature extraction; Image edge detection; Image segmentation; Skeleton; Vehicles; concave spots; occluded vehicles; segmentation; skeleton nodes;
Conference_Titel :
Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2012 Second International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4673-5034-1
DOI :
10.1109/IMCCC.2012.249