MULTIPLE MOVING OBJECTS TRACKING FOR VIDEO SURVEILLANCE SYSTEMS

Outline Foreground Regions Detection Features Extraction Tracking 1. Isolated object 2.Occlusion object.

Foreground Region Detection (Flow chart)

Foreground Regions Detection Background subtraction Binarization 2-stage median filter Update Background

Foreground Regions Detection (Result)

Features Extraction Centroid: Area: Mean intensity:

Isolated object tracking Mean intensity difference Area difference Weighted sum similarity function Distance similarity function Final

Dynamic Template Matching Template is created using previous frame (before occlusion) The correlation is then performed between the template and the current frame. The high score of the normalized cross- correlation matrix is occurred where the template is best correlated. The spatial position at which closes copy of the searched object is located. This spatial position represents the centroid of the tracked object in the current frame. The minimum distance from the object ’ s position in the previous frame. (have many high score)

Parameters Gray-level video imagery with frame rate 24 fps and frame size 320*240 pixels c 1 =0.6, c 2 =0.4 Range of the weighted sum function is [0.65, 0.81], and for the distance function is [3.1, 8.8] Th 1 =0.85, Th 2 =10

Experimental Results