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ICCV
2009
IEEE
2030views Computer Vision» more  ICCV 2009»
14 years 9 months ago
Robust Tracking-by-Detection using a Detector Confidence Particle Filter
We propose a novel approach for multi-person trackingby- detection in a particle filtering framework. In addition to final high-confidence detections, our algorithm uses the con...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...

Publication
353views
13 years 5 months ago
Online Multi-Person Tracking-by-Detection from a Single, Uncalibrated Camera
In this paper, we address the problem of automatically detecting and tracking a variable number of persons in complex scenes using a monocular, potentially moving, uncalibrated ca...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...
ECCV
2010
Springer
13 years 9 months ago
Cascaded Confidence Filtering for Improved Tracking-by-Detection
We propose a novel approach to increase the robustness of object detection algorithms in surveillance scenarios. The cascaded confidence filter successively incorporates constraint...
ICIP
2005
IEEE
14 years 6 months ago
Novel likelihood estimation technique based on boosting detector
This paper presents novel likelihood estimation to be used for particle filter based object tracking. The likelihood estimation is built upon cascade object detector trained with ...
Haijing Wang, Peihua Li, Tianwen Zhang
FGR
2006
IEEE
263views Biometrics» more  FGR 2006»
13 years 10 months ago
Robust Head Tracking Based on a Multi-State Particle Filter
This paper proposes a novel method for robust and automatic realtime head tracking by fusing face and head cues within a multi-state particle filter. Due to large appearance vari...
Yuan Li, Haizhou Ai, Chang Huang, Shihong Lao