Moving Object Detection Using Monocular Vision

  • Yin-Tien Wang
  • Kuo-Wei Chen
  • Ming-Jang Chiou
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 193)


This paper presents an algorithm for moving object detection (MOD) in robot visual simultaneous localization and mapping (SLAM). The algorithm is designed based on the defining epipolar constraint for the corresponding feature points on image plane. An essential matrix obtained using the state estimator is utilized to represent the epipolar constraint. Meanwhile, the method of speeded-up robust feature (SURF) is employed in the algorithm to provide a robust detection for image features as well as a better description of landmarks and of moving objects in visual SLAM system. Experiment is carried out on a hand-held monocular camera to validate the performances of the proposed algorithm. The results show that the integration of MOD and SURF is efficient for robot navigating in dynamic environments.


Moving object detection simultaneous localization and mapping speeded-up robust features monocular vision 


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Mechanical and Electro-Mechanical EngineeringTamkang UniversityNew TaipeiTaiwan

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