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

Lu Jin*, Mengyin Fu, Yi Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)3283-3290
Number of pages8
JournalJournal of Computational Information Systems
Volume10
Issue number8
DOIs
Publication statusPublished - 15 Apr 2014

Keywords

  • Driver assistant system
  • Information measurement
  • Mean shift
  • Unscented Kalman filter

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