The field of surveillance and forensics research is currently shifting focus and is now
showing an ever increasing interest in the task of people reidentification. This is the task of …

In recent years, vision based technologies have gained immense attention across academia-
industries to enable optimal surveillance solution for event monitoring, analysis and control …

Tracking multiple targets in nonoverlapping cameras are challenging since the observations
of the same targets are often separated by time and space. There might be significant …

This paper describes an original strategy for using a data-driven probabilistic motion model
into particle filter-based target tracking on video streams. Such a model is based on the local …

The moving target tracking results of multiple single cameras can rarely be efficiently
collaborated by using the current multi-camera target tracking algorithms, in the layout of …

Person reidentification (Re-ID) has been a problem recently faced in computer vision. Most
of the existing methods focus on body features which are captured in the scene with high …

This article describes an original strategy for enhancing current state-of-the-art trackers
through the use of motion priors, built as data-driven probabilistic motion models for moving …

Calibration, matching and tracking are major concerns to obtain 3D information consisting of
depth, direction and velocity. In finding depth, camera parameters and matched points are …

As the number of surveillance cameras deployed in public areas increasing rapidly,
automatic multi-target tracking in both a single camera and multiple non-overlapping …

This paper presents a particle filter-based approach for multiple target tracking in video
streams in single static cameras settings. We aim in particular to manage mid-dense crowds …