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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 classifiers,...
This paper provides comments to the paper "Visual Players Detection and Tracking in Soccer Matches". It was prepared as part of an experimental open review process for the 5th IEEE International Conference On Advanced Video and Signal Based Surveillance for which the author of this commentary paper acted as a reviewer. Due to the conference submission process, this comment was prepared for...
In this paper we propose a real-time algorithm for detecting and tracking moving objects in a video sequence. Based on the on-line boosting framework, our algorithm is able to detect an object as a member of a class, e.g. pedestrian, then a specific model for each instance of the class can be built on-line allowing at the same time robust tracking and recognition of the particular instance as it leaves...
In this paper, we employ the recent on-line boosting framework to fuse heterogeneous features for object detection and tracking in a video surveillance application. Detection and tracking are treated as a classification problem by an ensemble of weak classifiers built on heterogeneous feature types and updated on-line. We extend the on-line boosting framework by proposing an algorithm that builds...
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