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ICIAR
2005
Springer
14 years 29 days ago
A Novel Tracking Framework Using Kalman Filtering and Elastic Matching
A novel region-based multiple object tracking framework based on Kalman filtering and elastic matching is proposed. The proposed Kalman filtering-elastic matching model is genera...
Xingzhi Luo, Suchendra M. Bhandarkar
ICCV
2007
IEEE
14 years 9 months ago
What Can Casual Walkers Tell Us About A 3D Scene?
An approach for incremental learning of a 3D scene from a single static video camera is presented in this paper. In particular, we exploit the presence of casual people walking in...
Diego Rother, Kedar A. Patwardhan, Guillermo Sapir...
ICCV
2011
IEEE
12 years 7 months ago
Multi-View 3D Reconstruction for Scenes under the Refractive Plane with Known Vertical Direction
Images taken from scenes under water suffer distortion due to refraction. While refraction causes magnification with mild distortion on the observed images, severe distortions in...
Yao-Jen Chang, Tsuhan Chen
MVA
2008
196views Computer Vision» more  MVA 2008»
13 years 7 months ago
Evaluation of an appearance-based 3D face tracker using dense 3D data
The ability to detect and track human heads and faces in video sequences can be considered as the finest level of any video surveillance system. In this paper, we introduce a gener...
Fadi Dornaika, Angel Domingo Sappa
ICCV
2005
IEEE
14 years 1 months ago
KALMANSAC: Robust Filtering by Consensus
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...