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» Novel Observation Model for Probabilistic Object Tracking
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VLDB
2007
ACM
149views Database» more  VLDB 2007»
14 years 1 months ago
Probabilistic Skylines on Uncertain Data
Uncertain data are inherent in some important applications. Although a considerable amount of research has been dedicated to modeling uncertain data and answering some types of qu...
Jian Pei, Bin Jiang, Xuemin Lin, Yidong Yuan
ICCV
2009
IEEE
13 years 5 months ago
Robust facial feature tracking using selected multi-resolution linear predictors
This paper proposes a learnt data-driven approach for accurate, real-time tracking of facial features using only intensity information. Constraints such as a-priori shape models o...
Eng-Jon Ong, Yuxuan Lan, Barry Theobald, Richard H...
CVPR
2003
IEEE
14 years 9 months ago
Learning Object Intrinsic Structure for Robust Visual Tracking
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
Qiang Wang, Guangyou Xu, Haizhou Ai
MLMI
2005
Springer
14 years 1 months ago
Foreground Regions Extraction and Characterization Towards Real-Time Object Tracking
Abstract. Object localization and tracking are key issues in the analysis of scenes for video surveillance or scene understanding applications. This paper presents a contribution t...
José Luis Landabaso, Montse Pardàs
CVPR
2005
IEEE
14 years 9 months ago
A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences
This paper presents a dynamic conditional random field (DCRF) model to integrate contextual constraints for object segmentation in image sequences. Spatial and temporal dependenci...
Qiang Ji, Yang Wang 0002