A hybrid approach for image/video content representation and identification

Chaisorn, Lekha; Fu, Zixiang

doi:10.1109/iciea.2012.6360863

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…The average time taken by this method is much lesser than the other ones. Chaisorn and Fu [11] represented a hierarchical framework which works on the concept of content representation based on visuals (signature) with the algorithm for identification of content. It is a framework that works offline and online.…”

Section: Literature Surveymentioning

confidence: 99%

Identification of pattern and obtainment of content based images: an ephemeral and swift approach

Batra

Sharma

2015

CSIT

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The progressive web and computerized advancements have forced endless increment in the measure of visual data accessible to users. This trend prompted the advancement of exploration area where retrieval of images is done through the content of information which became familiar as CBIR (Content based image retrieval). CBIR frameworks are to a great extent utilized as a part of medicinal picture annotation, face recognition systems, security frameworks and so on. In this paper we will discuss about an efficient system for retrieving images faster since speed and precision are important as well as techniques to obtain better classification of images. To conquer the issue of extensive number of features extracted which obliges vast measure of memory and processing force we need to build a blend of 3 techniques(SURF, SVM and LDA) which best portray the information with adequate precision. Hence, we are using dimensionality reduction algorithm LDA in combination with SVM for the classification purpose and SURF which is quick and robust interest point detector.

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Section: Literature Surveymentioning

confidence: 99%

Identification of pattern and obtainment of content based images: an ephemeral and swift approach

Batra

Sharma

2015

CSIT

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“…A method from [15] is based on a spatial approach in which, the video is segmented in shots using hue and saturation color, keyframes are selected from the middle of the shots and then clustered to reduce the search space, signatures are generated using filtering on top of metaslices. Singular value decomposition (SVD) is used to detect shot changes and extract keyframes.…”

Section: Overview Of Previous Work In Video Signaturesmentioning

confidence: 99%

An HEVC compressed domain content-based video signature for copy detection and video retrieval

et al. 2014

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Video sharing platforms and social networks have been growing very rapidly for the past few years. The rapid increase in the amount of video content introduces many challenges in terms of copyright violation detection and video search and retrieval. Generating and matching content-based video signatures, or fingerprints, is an effective method to detect copies or "near-duplicate" videos. Video signatures should be robust to changes in the video features used to characterize the signature caused by common signal processing operations. Recent work has focused on generating video signatures based on the uncompressed domain. However, decompression is a computationally intensive operation. In large video databases, it becomes advantageous to create robust signatures directly from the compressed domain. The High Efficiency Video Coding (HEVC) standard has been recently ratified as the latest video coding standard and wide spread adoption is anticipated. We propose a method in which a content-based video signature is generated directly from the HEVC-coded bitstream. Motion vectors from the HEVC-coded bitstream are used as the features. A robust hashing function based on projection on random matrices is used to generate the hashing bits. A sequence of these bits serves as the signature for the video. Our experimental results show that our proposed method generates a signature robust to common signal processing techniques such as resolution scaling, brightness scaling and compression.

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Accurate Identification of Internet Video Traffic Using Byte Code Distribution Features

Xie

Deng

Peng

et al. 2018

Algorithms and Architectures for Parallel Processing

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A hybrid approach for image/video content representation and identification

Cited by 4 publications

References 12 publications

Identification of pattern and obtainment of content based images: an ephemeral and swift approach

Identification of pattern and obtainment of content based images: an ephemeral and swift approach

An HEVC compressed domain content-based video signature for copy detection and video retrieval

Accurate Identification of Internet Video Traffic Using Byte Code Distribution Features

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