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Andrey Kopylov
Researcher at Tula State University
Publications - 42
Citations - 205
Andrey Kopylov is an academic researcher from Tula State University. The author has contributed to research in topics: Image processing & Computer science. The author has an hindex of 7, co-authored 33 publications receiving 160 citations.
Papers
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Proceedings ArticleDOI
Elastic transformation of the image pixel grid for similarity based face identification
TL;DR: The proposed nonlinear transformation of one image plane relative to another by spatially constrained elastic matching of two pixel grids is proposed as a technique of measuring image similarity for the purpose of featureless face identification.
Journal ArticleDOI
Improved global motion estimation via motion vector clustering for video stabilization
Bo-Hao Chen,Andrey Kopylov,Shih-Chia Huang,Oleg Seredin,Roman Karpov,Sy-Yen Kuo,K. Robert Lai,Tan-Hsu Tan,Munkhjargal Gochoo,Damdinsuren Bayanduuren,Cihun-Siyong Gong,Patrick C. K. Hung +11 more
TL;DR: A novel video stabilization approach based on the shortest spanning path clustering algorithm for effective and reliable estimation of the global motion vectors is proposed, which achieves superior stabilized effectiveness compared with the other state-of-the-art approaches based on both qualitative and quantitative measurements.
Journal ArticleDOI
A skeleton features-based fall detection using microsoft kinect v2 with one class-classifier outlier removal
TL;DR: The proposed algorithm is based on the skeleton features encoding on the sequence of neighboring frames and support vector machine classifier, and a version of a cumulative sum method is applied for combining the individual decisions on the consecutive frames.
Proceedings ArticleDOI
Visibility Enhancement of Single Hazy Images Using Hybrid Dark Channel Prior
Yi-Jui Cheng,Bo-Hao Chen,Shih-Chia Huang,Sy-Yen Kuo,Andrey Kopylov,Oleg Seredint,Leonid M. Mestetskiy,Boris V. Vishnyakov,Y. V. Vizilter,O. V. Vygolov,Chia-Ruei Lian,Chi-Ting Wu +11 more
TL;DR: The overall results show that the proposed haze removal approach can recover haze-free images more effectively than can the other previous state-of-the-art haze removal approaches while avoiding over-saturation.
Optimization Techniques on Pixel Neighborhood Graphs for Image Processing.
TL;DR: Two versions of a high-speed minimization procedure are proposed for, respectively, discretely defined and quadratic objective functions.