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Adaptive object tracking based on vision sensor and milli-meter wave radar

  • Lu Jin*
  • , Mengyin Fu
  • , Yi Yang
  • *此作品的通讯作者
  • Ministry of Education in China
  • Beijing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

The object tracking for driver assistant system by the multi-sensors fusion has drawn much attention recently. With the complexity of space alignment, a new space alignment algorithm is proposed to project the object by millimeter wave radar onto the image plane. The method needs not to estimate interior and exterior parameters between two sensors. Considering alignment result as the measurement, a new tracking algorithm based on the Mean Shift with Unscented Kalman Filter and Information Measure of Multi-Scale Image is proposed. The Unscented Kalman Filter firstly is used to predict the initial iteration position for Mean Shift algorithm. After the object position is located by Mean Shift algorithm, the size of tracking window is adjusted adaptively through the size change ratio of adjacent frame. The results show that the proposed algorithm can track accurately the object whose size is gradually increasing or decreasing, and the algorithm also reduces the iteration times, the location time and the tracking error.

源语言英语
页(从-至)3283-3290
页数8
期刊Journal of Computational Information Systems
卷10
期8
DOI
出版状态已出版 - 15 4月 2014

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