By Tieniu Tan, Qiuqi Ruan, Shengjin Wang, Huimin Ma, Kaichang Di
This e-book constitutes the refereed complaints of the tenth chinese language convention on Advances in snapshot and pics applied sciences, IGTA 2015, held in Beijing, China, in June 2015. The 50 papers awarded have been rigorously reviewed and chosen from 138 submissions. they supply a discussion board for sharing new features of the progresses within the components of picture processing know-how, photo research und realizing, computing device imaginative and prescient and development acceptance, mammoth info mining, special effects and VR, picture know-how application.
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Extra resources for Advances in Image and Graphics Technologies: 10th Chinese Conference, IGTA 2015, Beijing, China, June 19-20, 2015, Proceedings
3. Splicing the forty Gabor representation images to form a big global image by scales variety with row and orientations variety with column. It denoted by: G2 D 4. Collecting each G2 D F0,0 = F4,7 F0,7 F4,7 (9) image of every face to form new images training set. 8. 5. Projecting the G2 D image to the subspace spanned by the eigenvectors to get the ultimate feature denoted as FG 2 DPCA . Fig. 1. Feature extraction procedure diagram of the proposed method 42 J. Yang and Y.
Video data Activity amount Average height Low-level Information Feature Information Combinations of the feature signal amount Semantic information Semantic Information Fig. 5. Semantic Output Process of Fish Behavior While thresholding, the activity amount and the average height are divided into three threshold levels: low, medium and high. According to the different output value group of the activity amount and the average height, we get the figure of the semantic network of the fish behavior described as Figure 6.
To reduce the dimensionality of traditional LBP features, far infrared face recognition based on LBP discriminant pattern was proposed by Xie et al , which gets a fixed subset from all LBP patterns. With regarding to infrared face recognition, an adaptive and fundamental feature extraction from all LBP patterns still is a big challenge [11, 12]. To address this issue, the adaptive dominant pattern is introduced to represent principle information in different infrared face images. Based on this novel dominant pattern, we construct the dissimilarity metric to depict the distance between two adaptive dominant pattern features.