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A real time object tracking approach for mobile robot visual servo control

Zhaoxiang Zhang, Ruhan Sa, Yunhong Wang

Year
2011
Citations
2

Abstract

A key problem of Image Based Visual Servo (IBVS) System is to track objects in image sequences. Thus, the tracking algorithm plays an important role in improving the efficiency of IBVS systems. In this paper, a novel tracking algorithm called Modified CamShift Guided Particle Filter (MCAMSGPF) is proposed, which interpolated Speeded-Up Robust Features (SURF) into the framework of conventional CamShift Guided Particle Filter (CAMSGPF) tracking method. This new algorithm outperforms conventional CAMSGPF and other baseline trackers with respect to tracking robustness in the clutter background of similar colors and occlusions. We also proposed a new system model to implement and test the new algorithm in a real time moving IBVS system, which is applied in a mobile robot with an on-board camera.

Keywords

Computer visionArtificial intelligenceParticle filterComputer scienceRobustness (evolution)BitTorrent trackerVideo trackingClutterEye trackingMobile robot

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