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Title page for etd-1119104-113452


URN etd-1119104-113452 Statistics This thesis had been viewed 3713 times. Download 1845 times.
Author Lung-Sheng Jang
Author's Email Address No Public.
Department Electrical Engineering
Year 2003 Semester 2
Degree Master Type of Document Master's Thesis
Language English Page Count 51
Title Detection and Tracking of Human in Dynamic Scenes
Keyword
  • motion estimation
  • motion detection
  • human tracking
  • human detection
  • human detection
  • human tracking
  • motion detection
  • motion estimation
  • Abstract ABSTRACT
    Detection and tracking human in image sequences is a fundamental and crucial research topic. It has vast applications in many visual systems, e.g. video surveillance, traffic monitoring, human detection, and video editing, etc. In this thesis, we aim at explore and implement a detection and tracking of human system in dynamic scenes.
    The system consists of four major blocks: (i) Dominant motion estimation: We adopt the hierarchical dominant motion estimation method in the form of a Gaussian pyramid to estimate the background motion. (ii) Motion detection: An efficient and effective method based on background subtraction is adopted to detect moving objects. (iii) Image blending: Once the dominant motion of the consecutive frames is obtained, we then use a triangular weighting function to blend overlapping regions into a panoramic background image. (iv) Tracking of moving objects: Finally, we utilize a set of three geometric features extracted from the detected moving objects to track moving object in complex environment.
    We demonstrate our tracking system with real-life image sequences. Experimental results show that our algorithm is fair robust and effective.
    Advisor Committee
  • Jia-Ching Cheng - advisor
  • Jiun-Shian Jou - co-chair
  • Yung-An Gau - co-chair
  • Files indicate access worldwide
    Date of Defense 2004-07-30 Date of Submission 2004-11-19


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