Ms. Hongyu Chen Profile

Hongyu Chen

at Shenyang Institute of Automation

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Publications (2)

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Proceedings Article | 17 April 2020 Paper

Part-based long-term tracking via multiple correlation filters

Hongyu Chen, Haibo Luo, Bin Hui, Zheng Chang, Miao He

Proceedings Volume 11455, 1145574 (2020) https://doi.org/10.1117/12.2565319

KEYWORDS: Computer vision technology, Monte Carlo methods, Detection and tracking algorithms, Optical tracking

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Compared with short-term tracking, long-term tracking is a more challenging task. It need to have the ability to capture the target in long-term sequences, and undergo the frequent disappearance and re-appearance of target. Therefore, long-term tracking is much closer to realistic tracking system. But few long-term tracking algorithms have been done and few promising performance have been shown. In this paper, we focus on long-term visual tracking framework based on parts with multiple correlation filters. First of all, multiple correlation filters have been applied to locate the target collaboratively and address the partial occlusion issue in a local search region. Based on the confidence score between the consecutive frames, our tracker determines whether the current tracking result is reliable or not. In addition, an online SVM detector is trained by sampling positive and negative samples around the reliable tracking target. The local-to-global search region strategy is adopted to adapt the short-term tracking and long-term tracking. When heavy occlusion or out-of-view causes the tracking failure, the re-detection module will be activated. Extensive experimental results on tracking datasets show that our proposed tracking method performs favorably against state-of-the-art methods in terms of accuracy, and robustness.

Proceedings Article | 15 October 2015 Paper

Infrared image enhancement based on human visual properties

Hongyu Chen, Bin Hui

Proceedings Volume 9674, 96742J (2015) https://doi.org/10.1117/12.2201173

KEYWORDS: Image enhancement, Infrared imaging, Infrared radiation, Visualization, Adaptive control, Image processing, Control systems, Image segmentation, Visible radiation, Image filtering

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With the development of modern military, infrared imaging technology is widely used in this field. However, limited by the mechanism of infrared imaging and the detector, infrared images have the disadvantages of low contrast and blurry edge by comparison with the visible image. These shortcomings lead infrared image unsuitable to be observed by both human and computer. Thus image enhancement is required. Traditional image enhancement methods on the application of infrared image, without taking into account the human visual properties, is not convenient for the human observation. This article purposes a new method that combines the layering idea with the human visual properties to enhance the infrared image. The proposed method relies on bilateral filtering to separate a base component, which contains the large amplitude signal and must be compressed, from a detail component, which must be expanded because it contains the small signal variations related to fine texture. The base component is mapped into the proper range which is 8-bit using the human visual properties, and the detail component is applied the method of adaptive gain control. Finally, the two parts are recombined and quantized to 8-bit domain. Experimental results show that this algorithm exceeds most current image enhancement methods in solving the problems of low contrast and blurry detail.

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