Multiple Person Tracking with Shadow Removal Using Adaptive Gaussian Mixture Model in Video Surveillance
Person detection in a video surveillance system is major concern in real world. Several application likes abnormal event detection, congestion analysis, human gait characterization, fall detection, person identification, gender classification and for elderly people. In this algorithm, we use GMM method in background subtraction for multi person detection because of Gaussian Mixture Model (GMM) model is one such popular method this give a real time object detection. There is still not robustly but Multi person tracking with shadow removal fill this gap, in this work, HOG-LBP hybrid approach with GMM algorithm is presented for Multi person tracking with Shadow removal.
Content
Person detection in a video surveillance system is major concern in real world. Several application likes abnormal event detection, congestion analysis, human gait characterization, fall detection, person identification, gender classification and for elderly people. In this algorithm, we use GMM method in background subtraction for multi person detection because of Gaussian Mixture Model (GMM) model is one such popular method this give a real time object detection. There is still not robustly but Multi person tracking with shadow removal fill this gap, in this work, HOG-LBP hybrid approach with GMM algorithm is presented for Multi person tracking with Shadow removal.
