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CVPR
2005
IEEE
16 years 6 months ago
A Statistical Field Model for Pedestrian Detection
This paper presents a new statistical model for detecting and tracking deformable objects such as pedestrians, where large shape variations induced by local shape deformation can ...
Ying Wu, Ting Yu, Gang Hua
158
Voted
AMDO
2006
Springer
15 years 8 months ago
Acquisition of Articulated Human Body Models Using Multiple Cameras
Abstract. Motion capture is an important application in different areas such as biomechanics, computer animation, and human-computer interaction. Current motion capture methods typ...
Aravind Sundaresan, Rama Chellappa
164
Voted
ICCV
2007
IEEE
16 years 6 months ago
Real-time Body Tracking Using a Gaussian Process Latent Variable Model
In this paper, we present a tracking framework for capturing articulated human motions in real-time, without the need for attaching markers onto the subject's body. This is a...
Shaobo Hou, Aphrodite Galata, Fabrice Caillette, N...
CVPR
2006
IEEE
15 years 10 months ago
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
CVPR
2000
IEEE
15 years 9 months ago
Multiscale Combination of Physically-Based Registration and Deformation Modeling
1 In this paper we present a novel multiscale approach to recovery of nonrigid motion from sequences of registered intensity and range images. The main idea of our approach is that...
Leonid V. Tsap, Dmitry B. Goldgof, Sudeep Sarkar