Colorogram: A Color Feature Descriptor for Human Blob Labeling

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 222)

Abstract

Tracking is one of the most important research fields for computer vision. Human Identity tracking is significant in the field of surveillance where a foolproof system is required that not only finds an existence of some person behaving suspicious but also his identification. In this paper, a novel feature descriptor by the name Colorogram has been proposed for labeling human blobs in videos. Two constraints were introduced into the system by way of color information and spatial spread of pixels in a new coordinate system. This feature descriptor helped in identifying/labeling human blobs with a priori knowledge of the scene. Two color spaces (HSV, RGB) and two histogram distance measures (Intersection, Euclidean) were considered for computation. The proposed Colorograms were compared with the conventional Histograms and Spatiograms. Experiments were conducted and the results have been tabulated. It was inferred that the new feature descriptor had classified humans with an acceptable precision and recall rates.

Keywords

Human identity Colorogram Tracking Feature extraction Histogram Blob Spatiogram 

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Copyright information

© Springer India 2013

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringKCG College of Technology, Anna UniversityChennaiIndia

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