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» A Probabilistic Background Model for Tracking
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CVPR
2012
IEEE
13 years 2 months ago
Robust object tracking via sparsity-based collaborative model
In this paper we propose a robust object tracking algorithm using a collaborative model. As the main challenge for object tracking is to account for drastic appearance change, we ...
Wei Zhong, Huchuan Lu, Ming-Hsuan Yang
3DIM
2007
IEEE
15 years 6 months ago
Tracking of Human Body Parts using the Multiocular Contracting Curve Density Algorithm
In this contribution we introduce the Multiocular Contracting Curve Density algorithm (MOCCD), a novel method for fitting a 3D parametric curve. The MOCCD is integrated into a tr...
Markus Hahn, Lars Krüger, Christian Wöhl...
KI
2005
Springer
15 years 5 months ago
A Probabilistic Multimodal Sensor Aggregation Scheme Applied for a Mobile Robot
Dealing with methods of human-robot interaction and using a real mobile robot, stable methods for people detection and tracking are fundamental features of such a system and requir...
Erik Schaffernicht, Christian Martin, Andrea Schei...
MOBIHOC
2009
ACM
16 years 11 days ago
Fault tolerant target tracking in sensor networks
In this paper, we present a Gaussian mixture model based approach to capture the spatial characteristics of any target signal in a sensor network, and further propose a temporally...
Min Ding, Xiuzhen Cheng
ICCV
2009
IEEE
14 years 9 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...