Multi-feature graph-based object tracking
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
MetroSurv: detecting events in subway stations
Multimedia Tools and Applications
Shadow removal for foreground segmentation
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Texture and space-time based moving objects segmentation and shadow removing
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
Shadow Casting Out Of Plane (SCOOP) Candidates for Human and Vehicle Detection in Aerial Imagery
International Journal of Computer Vision
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This paper proposes a novel shadow elimination method for solving the shadow occlusion problems of vehicle analysis. Different from traditional methods which only consider intensity properties in shadow modeling, this method introduces a new important feature to eliminate all unwanted shadows, i.e., lane line geometries. In this approach, a set of moving vehicles are first segmented from backgrounds by using a background subtraction technique. At this moment, each extracted vehicle may contain shadows which will cause the failure of further vehicle analysis. To remove these unwanted shadows, a histogram-based method is then proposed for detecting different lane dividing lines from video sequence. According to these lines, a line-based shadow modeling process is then applied for shadow elimination. Two kinds of lines are used here for shadow elimination, i.e., the ones parallel and vertical to lane directions, respectively. Different type of lines has different capabilities to eliminate different kinds of shadows. Experiments demonstrate that approximately 92% of shadows can be successfully eliminated from moving vehicles.