Multiple Perspective Object Tracking via Context-Aware Correlation Filter

Context - Aware Correlation Filter Tracker ( Supplementary Material )

Context - aware and Attentional Visual Object Tracking

Context-aware and Attentional Visual Object Tracking

Sequential Particle Filter for Multiple Object Tracking

Tracking objects in a scene under different degree of occlusions is still a challenge in computer vision. In this paper, we aim to tackle this problem with a jump observation model that includes both visible objects and occluded objects in a sequential particle filter tracking technique. The technique is extended from the sequential estimation method. An hierarchical structure is introduced to ...

Multiple object tracking with context awareness

Multiple people tracking is a key problem for many applications such as surveillance, animation or car navigation, and a key input for tasks such as activity recognition. In crowded environments occlusions and false detections are common, and although there have been substantial advances in recent years, tracking is still a challenging task. Tracking is typically divided into two steps: detecti...

CFNN: Correlation Filter Neural Network for Visual Object Tracking

Albeit convolutional neural network (CNN) has shown promising capacity in many computer vision tasks, applying it to visual tracking is yet far from solved. Existing methods either employ a large external dataset to undertake exhaustive pre-training or suffer from less satisfactory results in terms of accuracy and robustness. To track single target in a wide range of videos, we present a novel ...