NDLI: Learning similarity metrics for dynamic scene segmentation

Content Provider	IEEE Xplore Digital Library
Author	Teney, D. Brown, M. Kit, D. Hall, P.
Copyright Year	2015
Description	Author affiliation: Univ. of Bath, Bath, UK (Brown, M.; Kit, D.; Hall, P.) \|\| Carnegie Mellon Univ., Pittsburgh, PA, USA (Teney, D.)
Abstract	This paper addresses the segmentation of videos with arbitrary motion, including dynamic textures, using novel motion features and a supervised learning approach. Dynamic textures are commonplace in natural scenes, and exhibit complex patterns of appearance and motion (e.g. water, smoke, swaying foliage). These are difficult for existing segmentation algorithms, often violate the brightness constancy assumption needed for optical flow, and have complex segment characteristics beyond uniform appearance or motion. Our solution uses custom spatiotemporal filters that capture texture and motion cues, along with a novel metric-learning framework that optimizes this representation for specific objects and scenes. This is used within a hierarchical, graph-based segmentation setting, yielding state-of-the-art results for dynamic texture segmentation. We also demonstrate the applicability of our approach to general object and motion segmentation, showing significant improvements over unsupervised segmentation and results comparable to the best task specific approaches.
Starting Page	2084
Ending Page	2093
File Size	1989162
Page Count	10
File Format	PDF
ISSN	10636919
e-ISBN	9781467369640
DOI	10.1109/CVPR.2015.7298820
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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

Random ensemble metrics for object recognition

Pyramid Coding for Functional Scene Element Recognition in Video Scenes

A segmentation method for touching italic characters

Learning Similarity Metrics for Dynamic Scene Segmentation Supplementary material

Segmentation-Free Dynamic Scene Deblurring

Tiered scene labeling with dynamic programming

Video Co-segmentation for Meaningful Action Extraction

Dynamic Scene Deblurring

Learning hierarchical similarity metrics

Learning similarity metrics for dynamic scene segmentation

Similar Documents

Random ensemble metrics for object recognition

Pyramid Coding for Functional Scene Element Recognition in Video Scenes

A segmentation method for touching italic characters

Learning Similarity Metrics for Dynamic Scene Segmentation Supplementary material

Segmentation-Free Dynamic Scene Deblurring

Tiered scene labeling with dynamic programming

Video Co-segmentation for Meaningful Action Extraction

Dynamic Scene Deblurring

Learning hierarchical similarity metrics

Learning similarity metrics for dynamic scene segmentation