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BMVC
1998
13 years 9 months ago
Detection and Tracking of Very Small Low Contrast Objects
We present a Kalman tracking algorithm that can track a number of very small, low contrast objects through an image sequence taken from a static camera. The issues that we have ad...
D. Davies, Phil L. Palmer, Majid Mirmehdi
ROBOCUP
2007
Springer
180views Robotics» more  ROBOCUP 2007»
14 years 2 months ago
Improving Robot Self-localization Using Landmarks' Poses Tracking and Odometry Error Estimation
In this article the classical self-localization approach is improved by estimating, independently from the robot’s pose, the robot’s odometric error and the landmarks’ poses....
Pablo Guerrero, Javier Ruiz-del-Solar
CVPR
2008
IEEE
14 years 2 months ago
A theoretical analysis of linear and multi-linear models of image appearance
Linear and multi-linear models of object shape/appearance (PCA, 3DMM, AAM/ASM, multilinear tensors) have been very popular in computer vision. In this paper, we analyze the validi...
Yilei Xu, Amit K. Roy Chowdhury
CVPR
2004
IEEE
14 years 10 months ago
Multiple Kernel Tracking with SSD
Kernel-based objective functions optimized using the mean shift algorithm have been demonstrated as an effective means of tracking in video sequences. The resulting algorithms com...
Gregory D. Hager, Maneesh Dewan, Charles V. Stewar...
SIBGRAPI
2007
IEEE
14 years 2 months ago
Multiple Mice Tracking using a Combination of Particle Filter and K-Means
This paper presents a new approach to multiple objects tracking that combines particle filters and k-means. The approach has been tested under an important real world situation, ...
Wesley Nunes Gonçalves, João Bosco O...