loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Anurag Singh 1 ; Chee-Hung Henry Chu 2 and Michael A. Pratt 1

Affiliations: 1 University of Louisiana at Lafayette, United States ; 2 University of Louisiana at Lafayette and University of Louisiana at Lafayette, United States

Keyword(s): Video Saliency, Temporal Superpixels, Support Vector Machines, Saliency Flow.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Image Understanding ; Object Recognition ; Pattern Recognition ; Software Engineering ; Video Analysis

Abstract: Visual Saliency of a video sequence can be computed by combining spatial and temporal features that attract a user’s attention to a group of pixels. We present a method that computes video saliency by integrating these features: color dissimilarity, objectness measure, motion difference, and boundary score. We use temporal clusters of pixels, or temporal superpixels, to simulate attention associated with a group of moving pixels in a video sequence. The features are combined using weights learned by a linear support vector machine in an online fashion. The temporal linkage for superpixels is then used to find the saliency flow across the image frames. We experimentally demonstrate the efficacy of the proposed method and that the method has better performance when compared to state-of-the-art methods.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.226.226.30

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Singh, A.; Henry Chu, C. and A. Pratt, M. (2015). Learning to Predict Video Saliency using Temporal Superpixels. In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM; ISBN 978-989-758-077-2; ISSN 2184-4313, SciTePress, pages 201-209. DOI: 10.5220/0005206402010209

@conference{icpram15,
author={Anurag Singh. and Chee{-}Hung {Henry Chu}. and Michael {A. Pratt}.},
title={Learning to Predict Video Saliency using Temporal Superpixels},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM},
year={2015},
pages={201-209},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005206402010209},
isbn={978-989-758-077-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM
TI - Learning to Predict Video Saliency using Temporal Superpixels
SN - 978-989-758-077-2
IS - 2184-4313
AU - Singh, A.
AU - Henry Chu, C.
AU - A. Pratt, M.
PY - 2015
SP - 201
EP - 209
DO - 10.5220/0005206402010209
PB - SciTePress