Improved Gaussian Mixture Model for the Task of Object Tracking

International audience; This paper presents an object tracking system. Our goal is to create a real-time object tracker that can handle occlusions, track multiple objects that are rigid or deformable, and on indoor or outdoor sequences. This system is composed of two main modules: motion detection and object tracking. Motion detection is achieved using an improved Gaussian mixture model. Based on multiple hypothesis of object appearance, tracking is achieved on various levels. The core of this module uses regions local and global information to match these regions over the frame sequence. Then higher level instances are used to handle uncertainty, such as missmatches, objects disappearance, and occlusions. Finally, merges and splits are detected for further occlusions detection.