NDLI: Local Invariant Feature Tracks for high-level video feature extraction

Content Provider	IEEE Xplore Digital Library
Author	Mezaris, V. Dimou, A. Kompatsiaris, I.
Copyright Year	2010
Description	Author affiliation: Informatics and Telematics Institute / Centre for Research and Technology Hellas, 6th Km Charilaou-Thermi Road, 57001, Greece (Mezaris, V.; Dimou, A.; Kompatsiaris, I.)
Abstract	This paper builds upon previous work on local interest point detection and description to propose the extraction and representation of novel Local Invariant Feature Tracks (LIFT). These features compactly capture not only the spatial attributes of 2D local regions, as in SIFT and related techniques, but also their long-term trajectories in time. This and other desirable properties of LIFT allow the generation of Bags-of-Spatiotemporal-Words models that facilitate capturing the dynamics of video content, which is necessary for detecting high-level video features that by definition have a strong temporal dimension. Preliminary experimental evaluation and comparison of the proposed approach reveals promising results.
Starting Page	1
Ending Page	4
File Size	224996
Page Count	4
File Format	PDF
ISBN	9781424478484
e-ISBN	9788890532801
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-12
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Univ of Brescia
Subject Keyword	Histograms Computer vision Tracking Streaming media Feature extraction Cameras Trajectory
Content Type	Text
Resource Type	Article

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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
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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
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Local Invariant Feature Tracks for high-level video feature extraction