NDLI: User-oriented affective video content analysis

Content Provider	IEEE Xplore Digital Library
Author	Hanjalic, A. Li-Qun Xu
Copyright Year	2001
Description	Author affiliation: Dept. of Mediamatics, Delft Univ. of Technol., Netherlands (Hanjalic, A.)
Abstract	The article looks into a new direction in multimedia content analysis: the extraction and modeling of the affective content of an arbitrary video. The affective content is viewed as the amount of feeling/emotion contained in and mediated by a video toward a viewer. The ability to automatically extract video content of this nature will lead to a high level of personalization in broadcast delivery to private users, as well as considerably broadening the possibilities of efficiently handling and presenting large amounts of audio-visual data stored in emerging video databases. The technique we have developed uses the so-called "dimensional approach to affect" concept underlined by psychophysiology studies. Our computational method sets to represent the affective content as feature points in the so-called 2D emotion space. We manage to obtain time curves that represent the two affect dimensions (arousal and valence) for a video, considered respectively, from low-level video characteristics. Combining the two time curves results in the so-called affect curve that is regarded as a reliable representation of transitions from one feeling to another along a video, as perceived by a viewer. We illustrate the success of our technique on excerpts taken from an action movie and a typical soccer game, respectively.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Pattern Anal. & Machines Intelligence
Starting Page	50
Ending Page	57
File Size	705098
Page Count	8
File Format	PDF
ISBN	0769513549
DOI	10.1109/IVL.2001.990856
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-12-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Buffer storage Data mining Broadcasting Spatial databases Audio databases Psychology Motion pictures Games Information retrieval Signal analysis
Content Type	Text
Resource Type	Article

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

Story Board Based Video Manufacture System

MMSS: multi-modal story-oriented video summarization

Developing context model supporting spatial relations for semantic video retrieval

A Video Retrieval Algorithm Based on Affective Features

Content-Based Music Retrieval Using Beat Information

Utilizing affective analysis for efficient movie browsing

Major cast detection in video using both audio and visual information

Audio signal feature extraction and classification using local discriminant bases

Automatic caption localization in videos using salient points

User-oriented affective video content analysis

Similar Documents

Story Board Based Video Manufacture System

MMSS: multi-modal story-oriented video summarization

Developing context model supporting spatial relations for semantic video retrieval

A Video Retrieval Algorithm Based on Affective Features

Content-Based Music Retrieval Using Beat Information

Utilizing affective analysis for efficient movie browsing

Major cast detection in video using both audio and visual information

Audio signal feature extraction and classification using local discriminant bases

Automatic caption localization in videos using salient points

User-oriented affective video content analysis