Detection of Moving Cast Shadows for Object Segmentation

نویسندگان

  • Jürgen Stauder
  • Roland Mech
  • Jörn Ostermann
چکیده

To prevent moving shadows being misclassified as moving objects or parts of moving objects, this paper presents an explicit method for detection of moving cast shadows on a dominating scene background. Those shadows are generated by objects moving between a light source and the background. Moving cast shadows cause a frame difference between two succeeding images of a monocular video image sequence. For shadow detection, these frame differences are detected and classified into regions covered and regions uncovered by a moving shadow. The detection and classification assume plane background and a nonnegligible size and intensity of the light sources. A cast shadow is detected by temporal integration of the covered background regions while subtracting the uncovered background regions. The shadow detection method is integrated into an algorithm for two-dimensional (2-D) shape estimation of moving objects from the informative part of the description of the international standard ISO/MPEG-4. The extended segmentation algorithm compensates first apparent camera motion. Then, a spatially adaptive relaxation scheme estimates a change detection mask for two consecutive images. An object mask is derived from the change detection mask by elimination of changes due to background uncovered by moving objects and by elimination of changes due to background covered or uncovered by moving cast shadows. Results obtained with MPEG-4 test sequences and additional sequences show that the accuracy of object segmentation is substantially improved in presence of moving cast shadows. Objects and shadows are detected and tracked separately.

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عنوان ژورنال:
  • IEEE Trans. Multimedia

دوره 1  شماره 

صفحات  -

تاریخ انتشار 1999