Real-time recognition may be limited by scarce memory and computing resources for performing classification. Although, prior research has addressed the problem of training classif...
Ashish Kapoor, Simon Baker, Sumit Basu, Eric Horvi...
Our goal is to segment a video sequence into moving objects and the world scene. In recent work, spectral embedding of point trajectories based on 2D motion cues accumulated from ...
We present a hierarchical model for human activity recognition in entire multi-person scenes. Our model describes human behaviour at multiple levels of detail, ranging from low-le...
We consider the problem of finding a few representatives for a dataset, i.e., a subset of data points that efficiently describes the entire dataset. We assume that each data poi...
Recently sparse representation has been applied to visual tracker by modeling the target appearance using a sparse approximation over a template set, which leads to the so-called ...
In this paper, we study the problem of landmark recognition and propose to leverage 3D visual phrases to improve the performance. A 3D visual phrase is a triangular facet on the s...
Qiang Hao, Rui Cai, Zhiwei Li, Lei Zhang 0001, Yan...
Reconstructing realistic 3D hair geometry is challenging due to omnipresent occlusions, complex discontinuities and specular appearance. To address these challenges, we propose a ...
The k-NN graph has played a central role in increasingly popular data-driven techniques for various learning and vision tasks; yet, finding an efficient and effective way to con...
Jing Wang, Jingdong Wang, Gang Zeng, Zhuowen Tu, R...
This paper is aimed at calibrating the relative posture and position, i.e. extrinsic parameters, of a stationary camera against a 3D reference object which is not directly visible...
We describe an online approach to learn non-linear motion patterns and robust appearance models for multi-target tracking in a tracklet association framework. Unlike most previous...