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CVPR
1999
IEEE
14 years 9 months ago
A Multiple Hypothesis Approach to Figure Tracking
This paper describes a probabilistic multiple-hypothesis framework for tracking highly articulated objects. In this framework, the probability density of the tracker state is repr...
Tat-Jen Cham, James M. Rehg
BILDMED
2008
138views Algorithms» more  BILDMED 2008»
13 years 9 months ago
Level Set Segmentation of Lumbar Vertebrae Using Appearance Models
For the planning of surgical interventions of the spine exact knowledge about 3D shape and the local bone quality of vertebrae are of great importance in order to estimate the anch...
Karl D. Fritscher, Stefan Leber, Werner Schmö...
AMDO
2008
Springer
13 years 9 months ago
Accurate Human Motion Capture Using an Ergonomics-Based Anthropometric Human Model
Abstract. In this paper we present our work on markerless model-based 3D human motion capture using multiple cameras. We use an industry proven anthropometric human model that was ...
Jan Bandouch, Florian Engstler, Michael Beetz
CVPR
2005
IEEE
14 years 9 months ago
Appearance-Guided Particle Filtering for Articulated Hand Tracking
We propose a model-based tracking method, called appearance-guided particle filtering (AGPF), which integrates both sequential motion transition information and appearance informa...
Wen-Yan Chang, Chu-Song Chen, Yi-Ping Hung
CVPR
2007
IEEE
14 years 9 months ago
Change Detection in a 3-d World
This paper examines the problem of detecting changes in a 3-d scene from a sequence of images, taken by cameras with arbitrary but known pose. No prior knowledge of the state of n...
Thomas Pollard, Joseph L. Mundy