Abstract We propose a robust methodology for 3D modelbased markerless tracking of textured objects in monocular image sequences. The technique is based on mutual information maximi...
Abstract-This paper presents algorithms for vision-based detection and classification of vehicles in monocular image sequences of traffic scenes recorded by a stationary camera. Pr...
Surendra Gupte, Osama Masoud, Robert F. K. Martin,...
Augmenting cloth in real video is a challenging task because cloth performs complex motions and deformations and produces complex shading on the surface. Therefore, for a realisti...
A new technique is presented for computing 3D scene structure from point and line features in monocular image sequences. Unlike previous methods, the technique guarantees the comp...
In this paper the problem of obtaining 3D models from image sequences is addressed. The proposed method deals with uncalibrated monocular image sequences. No prior knowledge about...
This paper addresses the 3D tracking of pose and animation of the human face in monocular image sequences using deformable 3D models. For each frame, the proposed adaptation is sp...
Automatic recovery of 3D human pose from monocular image sequences is a challenging and important research topic with numerous applications. Although current methods are able to r...
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor pr...