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Viola et al. have introduced a fast object detection scheme based on a boosted cascade of haar-like features. In this paper, we introduce a novel ternary feature that enriches the diversity and the flexibility significantly over haar-like features. We also introduce a new genetic algorithm based method for training effective ternary features. Experimental results showed that the rejection rate can...
Hua et al. have proposed a stable and efficient tracking algorithm called ldquoK-means trackerrdquo[2, 3, 5]. This paper describes an adaptive non-target cluster center selection method that replaces the one used in k-means tracker where non-target cluster center are selected at fixed interval. Non-target cluster centers are selected from the ellipse that defines the area for searching the target...
Viola et al. have introduced a fast object detection scheme based on a boosted cascade of haar-like features. In this paper, we introduce a novel ternary feature that enriches the diversity and the flexibility significantly over haar-like features. We also introduce a new genetic algorithm (GA) based method for training effective ternary features through iterations of feature generation and selection...
In this paper, we present a clustering-based tracking algorithm for non-rigid object. Non-rigid object tracking is a challenging task because the target often appears as a concave shape or an object with apertures. In such cases, many background areas will be mixed into the tracking target, which are difficult to be removed by modifying the shape of the search area. Our algorithm realizes robust tracking...
In this paper, we present a clustering-based tracking algorithm for tracking people (e.g. hand, head, eyeball, body). A human body often appears as a concave object or an object with apertures. In this case, many background areas are mixed into the tracking target which are difficult to be removed by modifying the shape of the search area during tracking. This algorithm realizes the robust tracking...
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