Abstract Multi-Target Multi-Camera Tracking (MTMCT) tracks many people through video
taken from several cameras. Person Re-Identification (Re-ID) retrieves from a gallery images …

To help accelerate progress in multi-target, multi-camera tracking systems, we present (i) a
new pair of precision-recall measures of performance that treats errors of all types uniformly …

This paper presents a hierarchical composition approach for multi-view object tracking. The
key idea is to adaptively exploit multiple cues in both 2D and 3D, eg, ground occupancy …

Motivated by various delay sensitive applications, we address the problem of coordinating
the offloading decisions of wireless devices that periodically generate computationally …

Human activity recognition is central to many practical applications, ranging from visual
surveillance to gaming interfacing. Most approaches addressing this problem are based on …

Multi-view Multi-human association and tracking (MvMHAT) aims to track a group of people
over time in each view, as well as to identify the same person across different views at the …

Despite the advances in Human Activity Recognition, the ability to exploit the dynamics of
human body motion in videos has yet to be achieved. In numerous recent works …

In this paper, we propose a Spatio-temporal Attributed Parse Graph (ST-APG) to integrate
semantic attributes with trajectories for cross-view people tracking. Given videos from …

Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse
signals and images that enables sampling rates significantly below the classical Nyquist …

Cross-view multi-object tracking aims to link objects between frames and camera views with
substantial overlaps. Although cross-view multi-object tracking has received increased …