We propose a learning-based hierarchical approach of multi-target tracking from a single
camera by progressively associating detection responses into longer and longer track …

Video Tracking provides a comprehensive treatment of the fundamental aspects of algorithm
and application development for the task of estimating, over time, the position of objects of …

We propose a filtering framework for multitarget tracking that is based on the probability
hypothesis density (PHD) filter and data association using graph matching. This framework …

Video Surveillance (VS) systems are commonly deployed for real-time abnormal event
detection and autonomous video analytics. Video captured by surveillance cameras in real …

We propose a multi-target tracking algorithm based on the probability hypothesis density
(PHD) filter and data association using graph matching. The PHD filter is used to …

We propose a framework for multitarget tracking with feedback that accounts for scene
contextual information. We demonstrate the framework on two types of context-dependent …

This paper presents an adaptive tracking algorithm by learning hybrid object templates
online in video. The templates consist of multiple types of features, each of which describes …

Multiple object tracking is a fundamental subsystem of many higher level applications such
as traffic monitoring, people counting, robotic vision and many more. This paper explains in …

This paper presents an approach to extracting and using semantic layers from low altitude
aerial videos for scene understanding and object tracking. The input video is captured by …

CES dernieres années, la quantité de données vidéo enregistrées et sauvegardées de part
le monde a dramatiquement augmenté. Du fait de la disponibilité de caméras de moins en …