Feature tracking algorithm using neighborhood relaxation with multi-candidate pre-screening

Yen Kuang Chen, Yun Ting Lin, S. Y. Kung

Research output: Contribution to conferencePaperpeer-review

33 Scopus citations


Tracking of features in video sequences has many applications. Conventionally, the minimum displaced frame difference (referred to as DFD or residue) of a block of pixels is used as the criterion for tracking in block-matching algorithms (BMA). However, such a criterion often misses the true motion vectors, due to many practical factors, e.g. affine warping, image noises, object occlusion, lighting variation, and existence of multiple minimal DFD. Our goal in this paper is to find motion vectors of the features for object-based motion tracking, in which (1) any region of an object contains a good number of blocks, whose motion vectors exhibit certain consistency; (2) only true motion vectors for a few blocks per region are needed. Hence, we propose a new tracking method: (1) At the outset, we disqualify some of the reference blocks which are considered to be unreliable to track. (2) We adopt a multi-candidate pre-screening to provide some robustness in selecting motion candidates. (3) Assuming the true motion field is piecewise continuous, we determine the motion of a feature block by consulting all its neighboring blocks' directions. This allows a chance that a singular and erroneous motion vector may be corrected by its surrounding motion vectors (just like median filtering). Our method is also designed for tracking more flexible affine-type motions, such as rotation, zooming, sheering, etc. Finally, the performance improvement over other existing methods is demonstrated.

Original languageAmerican English
Number of pages4
StatePublished - Dec 1 1996
EventProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz
Duration: Sep 16 1996Sep 19 1996


ConferenceProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3)
CityLausanne, Switz

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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