Download PDF by Tieniu Tan, Qiuqi Ruan, Shengjin Wang, Huimin Ma, Kaichang: Advances in Image and Graphics Technologies: 10th Chinese

By Tieniu Tan, Qiuqi Ruan, Shengjin Wang, Huimin Ma, Kaichang Di

ISBN-10: 3662477904

ISBN-13: 9783662477908

ISBN-10: 3662477912

ISBN-13: 9783662477915

This e-book constitutes the refereed court cases of the tenth chinese language convention on Advances in photo and images applied sciences, IGTA 2015, held in Beijing, China, in June 2015. The 50 papers provided have been rigorously reviewed and chosen from 138 submissions. they supply a discussion board for sharing new points of the progresses within the parts of photo processing expertise, picture research und knowing, desktop imaginative and prescient and trend reputation, gigantic information mining, special effects and VR, snapshot expertise application.

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Additional info for Advances in Image and Graphics Technologies: 10th Chinese Conference, IGTA 2015, Beijing, China, June 19-20, 2015, Proceedings

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4. Recognition results with different partitioning modes Infrared Face Recognition Based on Adaptive Dominant Pattern of Local Binary Pattern 35 It can be seen from the Figure4 that recognition rates based on adaptive dominant pattern are higher than ones based on uniform pattern and discriminant pattern with all partitioning modes. From Figure4 one can see: partitioning modes can contribute to the better performance for all infrared face recognition methods based LBP. Especially for elapse-time database, the improving performance of adaptive dominant patterns is increasing with the blocks, which is superior to those methods based on uniform pattern and discriminant pattern.

So more and more researches focus on the multi-fish behavior. It is convenient for us to use computer vision technology to record the fish activities, but how to extract © Springer-Verlag Berlin Heidelberg 2015 T. Tan et al. ): IGTA 2015, CCIS 525, pp. 18–27, 2015. 1007/978-3-662-47791-5_3 Semantic Description of Fish Abnormal Behavior Based on the Computer Vision 19 the eigenvalue from the records is still challenging. Lu et al. [6] designed a kind of fish behavior automatic monitoring software (system) based on computer vision, by which changes in body color and swimming speed of fish group can be timely monitored to determine the unusual behavior of fish group.

The Union set of Si and Si are Si Si = Si1  Si2 (10) 1 2 To make the two adaptive features be of the same length, Ri and Ri are expanded 1 2 to ERi and ERi in the union set Si : ERi1 = Ri1  {(t , 0) | t ∉ Si1 , t ∈ Si2 } (11) ERi2 = Ri2  {(t , 0) | t ∉ Si2 , t ∈ Si1} (12) 1 2 After this expansion, the pattern bins in ERi are the same with the bins in ERi . Therefore, we can use traditional dissimilarity metrics to compute to the distance between the two features. In this paper, the metrics based on chi-square statistic [9] is 1 2 used to compute the distance between ERi and ERi .

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Advances in Image and Graphics Technologies: 10th Chinese Conference, IGTA 2015, Beijing, China, June 19-20, 2015, Proceedings by Tieniu Tan, Qiuqi Ruan, Shengjin Wang, Huimin Ma, Kaichang Di


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