NDLI: Place retrieval with graph-based place-view model

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Place retrieval with graph-based place-view model

Content Provider	ACM Digital Library
Author	Liu, Xianming Sun, Xiaoshuai Liu, Tianqiang Xu, Pengfei Ji, Rongrong Yao, Hongxun
Abstract	Places in movies and sitcoms could indicate higher-level semantic cues about the story scenarios and actor relations. This paper presents a novel unsupervised framework for efficient place retrieval in movies and sitcoms. We leverage face detection to filter out close-up frames from video dataset, and adopt saliency map analysis to partition background places from foreground actions. Consequently, we extract pyramid-based spatial-encoding correlogram from shot key frames for robust place representation. For effectively describing variant place appearances, we cluster key frames and model inter-cluster belonging of identical place by inside-shot association. Then hierarchical normalized cut is utilized over the association graph to differentiate physical places within videos and gain their multi-view representation as a tree structure. For efficient place matching in large-scale database, inversed indexing is applied onto the hierarchical graph structure, based on which approximate nearest neighbor search is proposed to largely accelerate search process. Experimental results on over 36-hour Friends sitcom database demonstrate the effectiveness, efficiency, and semantic revealing ability of our framework.
Starting Page	268
Ending Page	275
Page Count	8
File Format	PDF
ISBN	9781605583129
DOI	10.1145/1460096.1460141
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-10-30
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Large-scale retrieval Graph partition Key frame clustering Video analysis Inversed indexing Face detection Saliency map Place retrieval
Content Type	Text
Resource Type	Article

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