Browsing by Author "Wang Sheng-Jyh"

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Dynamic calibration method for single and multiple video capture devices
(2012-04-03)
Chen I-Hsien
;
Wang Sheng-Jyh
The present invention discloses a dynamic calibration method for a single and multiple video capture devices. The present invention can acquire the variations of the pan angle and tilt angle of a single video capture device according to the displacement of the feature points between successive images. For a plurality of video capture devices, the present invention includes the epipolar-plane constraint between a plurality of video capture devices to achieve the goal of dynamical calibration. The calibration method in the present invention does not require specific calibration patterns or complicated correspondence of feature points, and can be applied to surveillance systems with wide-range coverage.
Dynamic calibration method for single and multiple video capture devices
(2012-09-18)
Chen I-Hsien
;
Wang Sheng-Jyh
The present invention discloses a dynamic calibration method for a single and multiple video capture devices. The present invention can acquire the variations of the pan angle and tilt angle of a single video capture device according to the displacement of the feature points between successive images. For a plurality of video capture devices, the present invention includes the epipolar-plane constraint between a plurality of video capture devices to achieve the goal of dynamical calibration. The calibration method in the present invention does not require specific calibration patterns or complicated correspondence of feature points, and can be applied to surveillance systems with wide-range coverage.
Method for automatic detection and tracking of multiple targets with multiple cameras and system therefor
(2015-03-31)
Huang Ching-Chun
;
Wang Sheng-Jyh
A method for automatically detecting and tracking multiple targets in a multi-camera surveillance zone and system thereof. In each camera view of the system only a simple object detection algorithm is needed. The detection results from multiple cameras are fused into a posterior distribution, named TDP, based on the Bayesian rule. This TDP distribution represents a likelihood of presence of some moving targets on the ground plane. To properly handle the tracking of multiple moving targets with time, a sample-based framework which combines Markov Chain Monte Carlo (MCMC), Sequential Monte Carlo (SMC), and Mean-Shift Clustering, is provided. The detection and tracking accuracy is evaluated by both synthesized videos and real videos. The experimental results show that this method and system can accurately track a varying number of targets.