We contrast the performance of two methods of imposing constraints during the tracking of articulated objects, the first method preimposing the kinematic constraints during trackin...
We present a method for learning complex appearance mappings, such as occur with images of articulated objects. Traditional interpolation networks fail on this case since appearan...
This paper presents a framework for directly addressing issues arising from self-occlusions and ambiguities due to the lack of depth information in vector-based representations. V...
Recognizing categories of articulated objects in real-world scenarios is a challenging problem for today's vision algorithms. Due to the large appearance changes and intra-cla...
This paper presents a method of estimating both 3-D shapes and moving poses of an articulated object from a monocular image sequence. Instead of using direct depth data, prior loo...
Abstract. Tracking of articulated objects is a challenging task in Computer Vision. A highly target specific model can improve the robustness of the tracking by eliminating or red...
We present a method that is capable of tracking and estimating pose of articulated objects in real-time. This is achieved by using a bottom-up approach to detect instances of the ...
We propose an algorithm for accurate tracking of (articulated) objects using online update of appearance and shape. The challenge here is to model foreground appearance with histo...