tailieunhanh - Báo cáo hóa học: " Video Object Relevance Metrics for Overall Segmentation Quality Evaluation"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Video Object Relevance Metrics for Overall Segmentation Quality Evaluation | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 82195 Pages 1-11 DOI ASP 2006 82195 Video Object Relevance Metrics for Overall Segmentation Quality Evaluation Paulo Correia and Fernando Pereira Instituto Superior Tecnico - Instituto de Telecomunicaẹões Av. Rovisco Pais 1049-001 Lisboa Portugal Received 28 February 2005 Revised 31 May 2005 Accepted 31 July 2005 Video object segmentation is a task that humans perform efficiently and effectively but which is difficult for a computer to perform. Since video segmentation plays an important role for many emerging applications as those enabled by the MPEG-4 and MPEG-7 standards the ability to assess the segmentation quality in view of the application targets is a relevant task for which a standard or even a consensual solution is not available. This paper considers the evaluation of overall segmentation partitions quality highlighting one of its major components the contextual relevance of the segmented objects. Video object relevance metrics are presented taking into account the behaviour of the human visual system and the visual attention mechanisms. In particular contextual relevance evaluation takes into account the context where an object is found exploiting for instance the contrast to neighbours or the position in the image. Most of the relevance metrics proposed in this paper can also be used in contexts other than segmentation quality evaluation such as object-based rate control algorithms description creation or image and video quality evaluation. Copyright 2006 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION When working with image and video segmentation the major objective is to design an algorithm that produces appropriate segmentation results for the particular goals of the application addressed. Nowadays several applications exploit the representation of a video scene as a composition of video objects taking advantage of the .