NDLI: Semantic Feature Mining for Video Event Understanding

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Issue 1s(Special Issue on Smartphone-Based Interactive Technologies, Systems, and Applications and Special Issue on Extended Best Papers from ACM Multimedia 2014), October 2015

Issue 1, August 2015

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 11

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 10

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 9

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 8

Semantic Feature Mining for Video Event Understanding

Content Provider	ACM Digital Library
Author	Yang, Xiaoshan Zhang, Tianzhu Xu, Changsheng
Copyright Year	2016
Abstract	Content-based video understanding is extremely difficult due to the semantic gap between low-level vision signals and the various semantic concepts (object, action, and scene) in videos. Though feature extraction from videos has achieved significant progress, most of the previous methods rely only on low-level features, such as the appearance and motion features. Recently, visual-feature extraction has been improved significantly with machine-learning algorithms, especially deep learning. However, there is still not enough work focusing on extracting semantic features from videos directly. The goal of this article is to adopt unlabeled videos with the help of text descriptions to learn an embedding function, which can be used to extract more effective semantic features from videos when only a few labeled samples are available for video recognition. To achieve this goal, we propose a novel embedding convolutional neural network (ECNN). We evaluate our algorithm by comparing its performance on three challenging benchmarks with several popular state-of-the-art methods. Extensive experimental results show that the proposed ECNN consistently and significantly outperforms the existing methods.
Starting Page	1
Ending Page	22
Page Count	22
File Format	PDF
ISSN	15516857
e-ISSN	15516865
DOI	10.1145/2962719
Volume Number	12
Issue Number	4
Journal	ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-08-03
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Video recognition Event
Content Type	Text
Resource Type	Article
Subject	Hardware and Architecture Computer Networks and Communications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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