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Visual Tracking Under Motion Blur
2016
IEEE Transactions on Image Processing
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Specifically, a joint blur state estimation and multi-task reverse sparse learning framework are presented, where the closed-form solution of blur kernel and sparse code matrix is obtained simultaneously ...
Most existing tracking algorithms do not explicitly consider the motion blur contained in video sequences, which degrades their performance in real-world applications where motion blur often occurs. ...
for the multi-task model, which simultaneously obtains multiple sparse coding results and a single blur kernel of the candidates. • Based on the insight on the sparse code matrix, we propose an efficient ...
doi:10.1109/tip.2016.2615812
pmid:27723595
fatcat:lydxnubwineilnefbvkf25tz6q
Violent video detection based on MoSIFT feature and sparse coding
2014
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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To eliminate the feature noise, Kernel Density Estimation (KDE) is exploited for feature selection on the MoSIFT descriptor. ...
In order to obtain the highly discriminative video feature, this paper adopts sparse coding scheme to further process the selected MoSIFTs. ...
CONCLUSION This paper proposes an effective violent video detection approach based on the MoSIFT algorithm and the sparse coding scheme. ...
doi:10.1109/icassp.2014.6854259
dblp:conf/icassp/XuGYWY14
fatcat:b3jbtnjrbjc3xcbvfarhqe7yw4
WME-KSVD Dictionary Based Distributed Compressive Video Sensing
2017
International Journal of Multimedia and Ubiquitous Engineering
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The video reconstruction quality largely depends on the employed sparse representation which approximates the video frame by a sparse linear combination of items from an over-complete dictionary. ...
The two key frames which have been made motion estimation multiply the weighted factor to obtain the side information. Then the dictionary is generated by the side information and KSVD algorithm. ...
Introduction The conditional video coding systems based on motion-compensated-prediction, such as H.26x, MPEG, are highly asymmetrical since the computationally intensive motion prediction is performed ...
doi:10.14257/ijmue.2017.12.1.33
fatcat:sw2775yeqfdwrpurk3tadi5uhq
Video from a single coded exposure photograph using a learned over-complete dictionary
2011
2011 International Conference on Computer Vision
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Our approach has two important distinctions compared to previous works: (1) we achieve sparse representation of videos by learning an over-complete dictionary on video patches, and (2) we adhere to practical ...
To demonstrate the power of our approach, we have implemented a prototype imaging system with per-pixel coded exposure control using a liquid crystal on silicon (LCoS) device. ...
Sparse Representation via Learning In this section, we discuss the details of building a learned over-complete dictionary based sparse representation of videos, and reconstructing videos from a single ...
doi:10.1109/iccv.2011.6126254
dblp:conf/iccv/HitomiGGMN11
fatcat:fyn3lox5mfc75bkmjor2aq75ki
Multiplication-Free One-Bit Transform and Diamond Search Combination for Fast Binary Block Motion Estimation
2007
2007 IEEE 15th Signal Processing and Communications Applications
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Unification of sparse search patterns with low-bit representation motion estimation methods are rarely investigated and therefore one-bit transform based approaches are executed using full-search approach ...
Combination of multiplication-free one-bit transform based block estimation with the diamond sparse search pattern is presented is this paper. ...
Approximately more than half of the video compression time is consumed in motion estimation for many video coding methods [1] . ...
doi:10.1109/siu.2007.4298574
fatcat:fsgcz6xzb5d57itlxwl5w5w7ri
Progressive Dictionary Learning With Hierarchical Predictive Structure for Low Bit-Rate Scalable Video Coding
2017
IEEE Transactions on Image Processing
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For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers with a guarantee of reconstruction performance. ...
On the other hand, scalable extension of conventional hybrid motion compensation-discrete cosine transform (MC-DCT) framework has been widely studied for scalable video coding. ...
Inspired by sparse representation based on the patch-based overcomplete dictionary [33] , example-based approach [34] was developed for super-resolution based reconstruction for video coding. ...
doi:10.1109/tip.2017.2692882
pmid:28422683
pmcid:PMC5638692
fatcat:yrf6mgcpojezvjhmiuvmvqklne
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal
[article]
2020
arXiv
pre-print
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relying on the appearance of the coded key frames. ...
By learning to extract sparse motion pattern via a predictive model, the network elegantly leverages the feature representation to generate the appearance of to-be-coded frames via a generative model, ...
,m N } and a learned Motion Guided Generation Network (MGGN) will first estimate the motion flow among frames based on the decompressed sparse motion pattern. ...
arXiv:2001.03004v1
fatcat:5wkilmqmsvhhvet2xvoto7fwui
Low-complexity video compression and compressive sensing
2013
2013 Asilomar Conference on Signals, Systems and Computers
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To reduce video-encoder complexity, we present a CS-based video compression scheme. Modern video-encoder complexity arises mainly from the transformcoding and motion-estimation blocks. ...
Recovery process involves solving an 1-regularized optimization problem, which iteratively updates estimates for the video frames and motion within adjacent frames. ...
., motion estimation and transform coding in MPEG and H.264 video coding), and discarding the rest. ...
doi:10.1109/acssc.2013.6810345
dblp:conf/acssc/AsifFR13
fatcat:yuad4om4nvcs5pkkpm5wi7hwvq
Super-resolution Reconstruction of Noisy Video Image Based on Sparse Representation Algorithm
2019
Informatica (Ljubljana, Tiskana izd.)
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In this paper, the image super-resolution reconstruction (SRR) based on sparse representation was studied. ...
The results showed that the average PSNR value and average SSIM of the SRR processing method based on sparse representation were significantly higher than those of bicubic interpolation method; the quality ...
This paper first designed a SRR processing method based on sparse representation for a single image and then carried out SRR processing for the noisy video image. ...
doi:10.31449/inf.v43i3.2916
fatcat:r2rdhlo2crcz7dhwni45aija4i
Visual tracking by dictionary learning and motion estimation
2012
2012 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)
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Here, we utilize motion information in order to reduce this computation time by not calculating sparse codes for all the frames. ...
The proposed method combines sparse representation and motion estimation to track an object. Recently, sparse representation has gained much attention in signal processing and computer vision. ...
In this method, we compute the sparse codes for i-th frame and estimate the sparse code for the (i+1)-th frame. ...
doi:10.1109/isspit.2012.6621300
dblp:conf/isspit/JourablooBFSJ12
fatcat:ukegzy65pnggph2zt7wuczvpjq
Distributed compressed video sensing
2009
2009 16th IEEE International Conference on Image Processing (ICIP)
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This paper proposes a novel framework called Distributed Compressed Video Sensing (DISCOS) -a solution for Distributed Video Coding (DVC) based on the recently emerging Compressed Sensing theory. ...
Index Termsdistributed video coding, Wyner-Ziv coding, compressed sensing, compressive sensing, sparse recovery with decoder side information, structurally random matrices. ...
Our main original contributions in this work include • A novel model of interframe sparsity for video sequences; • Novel algorithms of sparsity-constraint block prediction, motion estimation and motion ...
doi:10.1109/icip.2009.5414631
dblp:conf/icip/DoCNNGT09
fatcat:sspdrzv66jgvnbr6z45lczmoxa
Distributed Compressed Video Sensing
2009
2009 43rd Annual Conference on Information Sciences and Systems
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This paper proposes a novel framework called Distributed Compressed Video Sensing (DISCOS) -a solution for Distributed Video Coding (DVC) based on the recently emerging Compressed Sensing theory. ...
Index Termsdistributed video coding, Wyner-Ziv coding, compressed sensing, compressive sensing, sparse recovery with decoder side information, structurally random matrices. ...
Our main original contributions in this work include • A novel model of interframe sparsity for video sequences; • Novel algorithms of sparsity-constraint block prediction, motion estimation and motion ...
doi:10.1109/ciss.2009.5054678
dblp:conf/ciss/DoCNNGT09
fatcat:keroyuxwwjdwxb3ekyw2p5gbxe
Multiresolution-based reconstruction for compressive spectral video sensing using a spectral multiplexing sensor
Inglés
2018
Revista UIS Ingenierías
Inglés
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The motion during the reconstruction produces artifacts that damages the entire data. In this work, a multiresolution-based reconstruction method for compressive spectral video sensing is proposed. ...
Arguello, "Multiresolution-based reconstruction for compressive spectral video sensing using a spectral multiplexing sensor," Rev. ...
de un sistema adaptativo de sensado compresivo de secuencias de video espectral" (VIE code 1891). ...
doi:10.18273/revuin.v17n1-2018020
fatcat:n5yqze6lgnhmhpwvthr2p6nx34
Learning Semantic Motion Patterns for Dynamic Scenes by Improved Sparse Topical Coding
2012
2012 IEEE International Conference on Multimedia and Expo
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Then the video is represented by a word-document hierarchical topic model through a generative process. Finally, an improved sparse topical coding approach is proposed for model learning. ...
In this paper, we propose a novel unsupervised approach to automatically explore motion patterns occurring in dynamic scenes under an improved sparse topical coding (STC) framework. ...
By representing a video as a topic model, an improved sparse topical coding framework is used to discover the semantic topical bases, with which each video clip can be sparsely reconstructed. ...
doi:10.1109/icme.2012.133
dblp:conf/icmcs/FuWLLM12
fatcat:4deovwmjujhl3hhueld352ouxi
Customized Video Summarization with Thumbnail Containers and 2D CNN
2024
International Journal of Advanced Research in Science, Communication and Technology
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This project focuses on acquiring customized video summaries using thumbnail container-based summarization framework and 2D CNN model to select and extract specific features from thumbnails. ...
We aim on developing a user interactive customized video summarization tool which will be trained utilizing diverse datasets leading to the generation of personalized video summaries for feature-length ...
The video summarization process employs various keyframe extraction techniques, including shot boundary-based, clustering-based, motion-based, sparse representation-based, and deep learning-based methods ...
doi:10.48175/ijarsct-15397
fatcat:24vrdln6ojbhxi2iqmzfgkajo4
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