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  1. Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
  2. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 9
  3. Issue 2, May 2013
  4. Effective transfer tagging from image to video
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ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 10
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 9
Issue 1s(Special Sections on the 20th Anniversary of ACM International Conference on Multimedia, Best Papers of ACM Multimedia 2012), October 2013
Issue 3, June 2013
Issue 2, May 2013
Human perception of haptic-to-video and haptic-to-audio skew in multimedia applications
A reward-and-punishment-based approach for concept detection using adaptive ontology rules
Identity verification based on handwritten signatures with haptic information using genetic programming
Multifeature analysis and semantic context learning for image classification
Modeling the effect of user interactions on mesh-based P2P VoD streaming systems
Effective transfer tagging from image to video
APRICOD: An access-pattern-driven distributed caching middleware for fast content discovery of noncontinuous media access
Issue 1, February 2013
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 8
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 7
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 7S
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 6
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 5
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 4
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 3
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 2
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 1

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Effective transfer tagging from image to video

Content Provider ACM Digital Library
Author Yang, Yang Yang, Yi Shen, Heng Tao
Copyright Year 2013
Abstract Recent years have witnessed a great explosion of user-generated videos on the Web. In order to achieve an effective and efficient video search, it is critical for modern video search engines to associate videos with semantic keywords automatically. Most of the existing video tagging methods can hardly achieve reliable performance due to deficiency of training data. It is noticed that abundant well-tagged data are available in other relevant types of media (e.g., images). In this article, we propose a novel video tagging framework, termed as Cross-Media Tag Transfer (CMTT), which utilizes the abundance of well-tagged images to facilitate video tagging. Specifically, we build a “cross-media tunnel” to transfer knowledge from images to videos. To this end, an optimal kernel space, in which distribution distance between images and video is minimized, is found to tackle the domain-shift problem. A novel cross-media video tagging model is proposed to infer tags by exploring the intrinsic local structures of both labeled and unlabeled data, and learn reliable video classifiers. An efficient algorithm is designed to optimize the proposed model in an iterative and alternative way. Extensive experiments illustrate the superiority of our proposal compared to the state-of-the-art algorithms.
Starting Page 1
Ending Page 20
Page Count 20
File Format PDF
ISSN 15516857
e-ISSN 15516865
DOI 10.1145/2457450.2457456
Volume Number 9
Issue Number 2
Journal ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2013-05-10
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Video tagging Cross media Semi-supervised learning Transfer learning
Content Type Text
Resource Type Article
Subject Hardware and Architecture Computer Networks and Communications
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