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» Novel Observation Model for Probabilistic Object Tracking
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3DIM
2007
IEEE
14 years 4 months ago
Dense Depth and Color Acquisition of Repetitive Motions
Modeling dynamic scenes is a challenging problem faced by applications such as digital content generation and motion analysis. Fast single-frame methods obtain sparse depth sample...
Yi Xu, Daniel G. Aliaga
MVA
2007
211views Computer Vision» more  MVA 2007»
13 years 11 months ago
Shadow Elimination in Traffic Video Segmentation
Shadow detection is critical for robust and reliable vision-based systems for traffic vision analysis. Shadow points are often misclassified as object points causing errors in loc...
Hong Liu, Jintao Li, Qun Liu, Yueliang Qian
ECCV
2004
Springer
15 years 1 days ago
Human Pose Estimation Using Learnt Probabilistic Region Similarities and Partial Configurations
Abstract. A model of human appearance is presented for efficient pose estimation from real-world images. In common with related approaches, a high-level model defines a space of co...
Timothy J. Roberts, Stephen J. McKenna, Ian W. Ric...
CVPR
2006
IEEE
15 years 5 days ago
Robust Fragments-based Tracking using the Integral Histogram
We present a novel algorithm (which we call "FragTrack") for tracking an object in a video sequence. The template object is represented by multiple image fragments or pa...
Amit Adam, Ehud Rivlin, Ilan Shimshoni
FGR
2000
IEEE
163views Biometrics» more  FGR 2000»
14 years 2 months ago
Tracking Interacting People
A computer vision system for tracking multiple people in relatively unconstrained environments is described. Trackerformed at three levels of abstraction: regions, people and grou...
Stephen J. McKenna, Sumer Jabri, Zoran Duric, Harr...