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  • 标题:NONRETINOTOPIC PARTICLE FILTER FOR VISUAL TRACKING
  • 本地全文:下载
  • 作者:ALEXANDER A S GUNAWAN ; ITO WASITO
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2014
  • 卷号:63
  • 期号:1
  • 出版社:Journal of Theoretical and Applied
  • 摘要:Visual tracking is the problem of using visual sensor measurements to determine location and path of target object. One of big challenges for visual tracking is full occlusion. When full occlusions are present, image data alone can be unreliable, and is not sufficient to detect the target object. The developed tracking algorithm is based on bootstrap particle filter and using color feature target. Furthermore the algorithm is modified using nonretinotopic concept, inspired from the way of human visual cortex handles occlusion by constructing nonretinotopic layers. We interpreted the concept by using past tracking memory about motion dynamics rather than current measurement when quality level of tracking reliability below a threshold. Using experiments, we found (i) the performance of the object tracking algorithm in handling occlusion can be improved using nonretinotopic concept, (ii) dynamic model is crucial for object tracking, especially when the target object experienced occlusion and maneuver motions, (iii) the dependency of the tracker performance on the accuracy of tracking quality threshold when facing illumination challenge. Preliminary experimental results are provided.
  • 关键词:Visual Tracking; Full Occlusion; Bootstrap Particle Filter; Color; Nonretinotopic; Tracking Quality Threshold
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