Chenglizhao Chen

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Salient motion detection is vital for security surveillance, pattern and motion recognition, traffic control, human–computer interaction, etc. Although such a subject has been very well investigated for analysis of stationary videos, many technical challenges still prevail when correctly handling and analyzing nonstationary videos recorded by hand-hold and(More)
This paper advocates a novel multiscale, structure-sensitive saliency detection method, which can distinguish multilevel, reliable saliency from various natural pictures in a robust and versatile way. One key challenge for saliency detection is to guarantee the entire salient object being characterized differently from nonsalient background. To tackle this,(More)
Object tracking in video is vital for security surveillance, pattern and motion recognition, traffic control, augmented reality, human-computer interaction, etc. Despite the rapid growth of various techniques in recent years, certain technical challenges still exist in terms of efficiency, accuracy, and robustness. To ameliorate, this paper suggests a novel(More)
This paper advocates a novel video saliency detection method based on the spatial-temporal saliency fusion and low-rank coherency guided saliency diffusion. In sharp contrast to the conventional methods, which conduct saliency detection locally in a frame-by-frame way and could easily give rise to incorrect low-level saliency map, in order to overcome the(More)
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