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Titlebook: Computer Vision and Image Processing; 5th International Co Satish Kumar Singh,Partha Roy,P. Nagabhushan Conference proceedings 2021 The Edi

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书目名称Computer Vision and Image Processing
副标题5th International Co
编辑Satish Kumar Singh,Partha Roy,P. Nagabhushan
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Computer Vision and Image Processing; 5th International Co Satish Kumar Singh,Partha Roy,P. Nagabhushan Conference proceedings 2021 The Edi
描述This three-volume set (CCIS 1367-1368) constitutes the refereed proceedings of the 5th International Conference on Computer Vision and Image Processing, CVIP 2020, held in Prayagraj, India, in December 2020. Due to the COVID-19 pandemic the conference was partially held online. .The 134 papers papers were carefully reviewed and selected from 352 submissions. The papers present recent research on such topics as biometrics, forensics, content protection, image enhancement/super-resolution/restoration, motion and tracking, image or video retrieval, image, image/video processing for autonomous vehicles, video scene understanding, human-computer interaction, document image analysis, face, iris, emotion, sign language and gesture recognition, 3D image/video processing, action and event detection/recognition, medical image and video analysis, vision-based human GAIT analysis, remote sensing, and more..
出版日期Conference proceedings 2021
关键词artificial intelligence; color image processing; computer hardware; computer networks; computer systems;
版次1
doihttps://doi.org/10.1007/978-981-16-1092-9
isbn_softcover978-981-16-1091-2
isbn_ebook978-981-16-1092-9Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Sign Language Recognition Using Cluster and Chunk-Based Feature Extraction and Symbolic Representatroposed methods namely Chunk-based and Cluster-based feature representation techniques in order to extract the desired keyframes. The features are extracted based on hands and head local centroid characteristics such as velocity, magnitude and orientation. A set of experiments are conducted on a lar
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Action Recognition in Haze Using an Efficient Fusion of Spatial and Temporal Features, actions in hazy videos. This paper proposes a novel unified model for action recognition in hazy video using an efficient combination of a Convolutional Neural Network (CNN) for obtaining the dehazed video first, followed by extracting spatial features from each frame, and a deep bidirectional LSTM
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Human Action Recognition from 3D Landmark Points of the Performer,rk points of the performer in recognizing action, is relatively less explored area of research due to the challenge involved in the process of extracting 3D landmark points from single view of the performers. With the recent advancements in the area of 3D landmark point detection, exploiting the lan
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A Combined Wavelet and Variational Mode Decomposition Approach for Denoising Texture Images,g the process of denoising. In this paper, we present a combined wavelet decomposition and Variational Mode Decomposition (VMD) approach to effectively denoise texture images while preserving the edges and fine-scale textures. The performance of the proposed method is compared with that of wavelet d
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Two-Image Approach to Reflection Removal with Deep Learning,ire certain conditions to be fulfilled. Recent advancements of deep learning in many fields have revolutionized these traditional approaches. Using input images more than one reduces the ill-posedness of the problem statement. Standard assumption in numerous methods assumes background is stationary
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Feature Selection and Feature Manifold for Age Estimation,ods, appearance features are projected onto a discriminant aging subspace and the age estimation is performed on the aging subspace. In these methods the manifold is learn from the gray intensity images. We propose a feature based discriminant manifold learning and feature selection scheme for robus
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