Tracking of Objects in Video Scenes with Time Varying Content

Tracking of Objects in Video Scenes with Time Varying Content

We propose a method for tracking of objects contained in video sequences. Each video object is represented by a set of polygonal regions. A bottom up approach (spatial segmentation/motion estimation) is applied for the initialisation of the method, a limited human interaction is used to build the semantic map of the first frame in video sequence. The tracking of this model along a video sequenc...

Object tracking in video scenes

Tracking Multiple Objects in Complex Scenes

Automatic video surveillance-based security is one of the most dynamically developing segment of the security industry. There has been a large progress of related vision hardware in the recent years, however, methods used to detect and monitor moving objects still lack the robustness to handle specific events occurring in complex scenes. In this paper we propose an algorithm to resolve occlusio...

Content-Based Retrieval of Video Surveillance Scenes

A novel method for content-based retrieval of surveillance video data is presented. The study starts from the realistic assumption that the automatic feature extraction is kept simple, i.e. only segmentation and low-cost filtering operations have been applied. The solution is based on a new and generic dissimilarity measure for discriminating video surveillance scenes. This weighted compound me...

Online multiple people tracking-by-detection in crowded scenes

Multiple people detection and tracking is a challenging task in real-world crowded scenes. In this paper, we have presented an online multiple people tracking-by-detection approach with a single camera. We have detected objects with deformable part models and a visual background extractor. In the tracking phase we have used a combination of support vector machine (SVM) person-specific classifie...