Paper
3 October 2008 Performance analysis of a modified moving shadow elimination method developed for indoor scene activity tracking
Author Affiliations +
Proceedings Volume 7119, Optics and Photonics for Counterterrorism and Crime Fighting IV; 71190A (2008) https://doi.org/10.1117/12.800376
Event: SPIE Security + Defence, 2008, Cardiff, Wales, United Kingdom
Abstract
Moving shadow detection is an important step in automated robust surveillance systems in which a dynamic object is to be segmented and tracked. Rejection of the shadow region significantly reduces the erroneous tracking of non-target objects within the scene. A method to eliminate such shadows in indoor video sequences has been developed by the authors. The objective has been met through the use of a pixel-wise shadow search process that utilizes a computational model in the RGB colour space to demarcate the moving shadow regions from the background scene and the foreground objects. However, it has been observed that the robustness and efficiency of the method can be significantly enhanced through the deployment of a binary-mask based shadow search process. This, in turn, calls for the use of a prior foreground object segmentation technique. The authors have also automated a standard foreground object segmentation technique through the deployment of some popular statistical outlier-detection based strategies. The paper analyses the performance i.e. the effectiveness as a shadow detector, discrimination potential, and the processing time of the modified moving shadow elimination method on the basis of some standard evaluation metrics.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bhargav Kumar Mitra, Muhammad Kamran Fiaz, Ioannis Kypraios, Philip Birch, Rupert Young, and Chris Chatwin "Performance analysis of a modified moving shadow elimination method developed for indoor scene activity tracking", Proc. SPIE 7119, Optics and Photonics for Counterterrorism and Crime Fighting IV, 71190A (3 October 2008); https://doi.org/10.1117/12.800376
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Cited by 2 scholarly publications.
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KEYWORDS
RGB color model

Video

Image segmentation

Distortion

Surveillance systems

Video processing

Binary data

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