Motion detection using periodic background estimation subtraction method

This paper proposed a motion detection system using periodic background estimation subtraction method for outdoor illumination condition using MATLAB. The proposed method is robust to illumination change effect, change in background and noise. The method basically used background subtraction. The background image is estimated at every 0.8 second when the sum of absolute difference (SAD) is less than the motion threshold. The input image is luminance normalize before background subtraction. The results were converted into binary image by autothreshold and enhanced the results with dilation and erosion. Blobs were created for each motion objects. Experiment results of using background image estimated by periodic background estimation demonstrate their robustness and effectiveness in background subtraction for real world scene

Occlusion handling in multiple people tracking

Object tracking with occlusion handling is a challenging problem in automated video surveillance. Occlusion handling and tracking have always been considered as separate modules. We have proposed an automated video surveillance system, which automatically detects occlusions and perform occlusion handling, while the tracker continues to track resulting separated objects. A new approach based on sub-blobbing is presented for tracking objects accurately and steadily, when the target encounters occlusion in video sequences. We have used a feature-based framework for tracking, which involves feature extraction and feature matching