2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)最新文献_第9页

Complete visual metrology using relative affine structure 使用相对仿射结构的完整视觉计量

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776265

Adersh Miglani, Sumantra Dutta Roy, S. Chaudhury, J. B. Srivastava

引用次数: 1

Adaptive BPSO based feature selection and skin detection based background removal for enhanced face recognition 基于自适应粒子群算法的特征选择和基于皮肤检测的背景去除增强人脸识别

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776226

Mayukh Sattiraju Student, Vikram Manikandan M Student, K. Manikantan, Associate Professor, S. Ramachandran

{"title":"Adaptive BPSO based feature selection and skin detection based background removal for enhanced face recognition","authors":"Mayukh Sattiraju Student, Vikram Manikandan M Student, K. Manikantan, Associate Professor, S. Ramachandran","doi":"10.1109/NCVPRIPG.2013.6776226","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2013.6776226","url":null,"abstract":"Face recognition under varying background and pose is challenging, and extracting background and pose invariant features is an effective approach to solve this problem. This paper proposes a skin detection-based approach for enhancing the performance of a Face Recognition (FR) system, employing a unique combination of Skin based background removal, Discrete Wavelet Transform (DWT), Adaptive Multi-Level Threshold Binary Particle Swarm Optimization (ABPSO) and an Error Control Feedback (ECF) loop. Skin based background removal is used for efficient background removal and ABPSO-based feature selection algorithm is used to search the feature space for the optimal feature subset. The ECF loop is used to neutralize pose variations. Experimental results, obtained by applying the proposed algorithm on Color FERET and CMUPIE face databases, show that the proposed system outperforms other FR systems. A significant increase in the recognition rate and substantial reduction in the number of features are observed.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126617337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

STAR: A Content Based Video Retrieval system for moving camera video shots STAR:一个基于内容的视频检索系统，用于移动摄像机视频拍摄

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776267

C. Chattopadhyay, Sukhendu Das

引用次数: 11

Word recognition in natural scene and video images using Hidden Markov Model 基于隐马尔可夫模型的自然场景和视频图像的词识别

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776157

Sangheeta Roy, P. Roy, P. Shivakumara, U. Pal

引用次数: 7

Monitoring a large surveillance space through distributed face matching 通过分布式人脸匹配实现对大监控空间的监控

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776185

Richa Mishra, Prasanna Kumar, S. Chaudhury, I. Sreedevi

引用次数: 14

Augmented paper system: A framework for User's Personalized Workspace 增强纸张系统:用户个性化工作空间的框架

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776182

Kavita Bhardwaj, S. Chaudhury, Sumantra Dutta Roy

引用次数: 4

Cursive stroke sequencing for handwritten text documents recognition 草书笔划排序手写文本文件识别

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776232

S. Panwar, N. Nain

{"title":"Cursive stroke sequencing for handwritten text documents recognition","authors":"S. Panwar, N. Nain","doi":"10.1109/NCVPRIPG.2013.6776232","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2013.6776232","url":null,"abstract":"Text segmentation can be defined as the process of splitting the images of handwritten text document into pieces corresponding to single lines, words and character. This is a very challenging task because in handwritten documents curved text lines appear frequently with different skew and slant angles. After segmentation of word or stroke, also defined as finding the connected components in handwritten text document, we have to sequence the strokes according to the document so that the meaning of the document is preserved. In this paper, We use bottom up grouping approach for segmentation. We have used a novel connectivity strength parameter with depth first search approach for extraction of connected components of the same line from complete connected components of the given document. The exact sequence of connected components is stored in the sequential vector which contains the label of the components. The proposed cursive stroke sequencing technique is implemented and tested on a benchmark IAM database providing encouraging results. Quantitative analysis also shows that this approach gives better results compared to existing segmentation techniques and overcomes the problems encountered in Hill-and-dale writing styles and overlapped and touched lines. The accuracy of the proposed sequencing technique is 98%.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"700 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122986296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Digital image tampering detection and localization using singular value decomposition technique 基于奇异值分解技术的数字图像篡改检测与定位

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776160

V. Mall, A. Roy, S. Mitra

引用次数: 6

Temporally scalable compression of animation geometry 动画几何的时间可伸缩压缩

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776263

Sanjib Das, H. ShahJaimeen, P. Bora

{"title":"Temporally scalable compression of animation geometry","authors":"Sanjib Das, H. ShahJaimeen, P. Bora","doi":"10.1109/NCVPRIPG.2013.6776263","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2013.6776263","url":null,"abstract":"Animation geometry compression involves compressing the geometry data of dynamic three-dimensional (3D) triangular meshes representing the animation frames. The scalability issue of geometry compression addresses compressing the geometry in a single scale and decompressing it in multiple scales. One of the algorithms for animation geometry compression employs the skinning based motion prediction of vertices and the temporal wavelet transform (TWT) on the prediction errors. This paper presents an encoder and a decoder structure for achieving temporally scalable implementation of the algorithm. The frame-wise prediction errors due to motion based clustering of a group of affine transformed vertices are converted into a layered structure of the frames using the TWT. The affine transformation data of vertices, weights corresponding to each cluster of vertices and the wavelet coefficients of the prediction errors are quantized and encoded using the entropy coding. The resulting bit-stream is arranged in a layered structure to achieve temporal scalability. The base layer consists of the connectivity coded first frame, indices of the clusters of vertices, weights corresponding to each cluster of a vertex, the approximation sub-band of prediction error and the affine transformations corresponding to the approximation frames. The enhancement layers consist of the detailed sub-bands of prediction error and the affine transformations corresponding to the detailed frames. The scalable encoder and decoder are tested on some standard animation sequences and the experimental results show good performance in terms of scalable rates and distortions.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"321 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121681621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatio-temporal feature based VLAD for efficient video retrieval 基于时空特征的VLAD高效视频检索

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI: 10.1109/NCVPRIPG.2013.6776268

M. K. Reddy, Sahil Arora, R. Venkatesh Babu

引用次数: 6