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Driven by the significant advancements in technology and social issues suchas security management, there is a strong need for Smart Surveillance System inour society today. One of the key features of a Smart Surveillance System isefficient human detection and counting such that the system can decide andlabel events on its own. In this paper we propose a new, novel and robustmodel, The Omega Model, for detecting and counting human beings present in thescene. The proposed model employs a set of four distinct descriptors foridentifying the unique features of the head, neck and shoulder regions of aperson. This unique head neck shoulder signature given by the Omega Modelexploits the challenges such as inter person variations in size and shape ofpeoples head, neck and shoulder regions to achieve robust detection of humanbeings even under partial occlusion, dynamically changing background andvarying illumination conditions. After experimentation we observe and analyzethe influences of each of the four descriptors on the system performance andcomputation speed and conclude that a weight based decision making systemproduces the best results. Evaluation results on a number of images indicatethe validation of our method in actual situation.

Omega Model for Human Detection and Counting for application in Smart Surveillance System