Content-based object movie retrieval and relevance feedbacks

Cheng Chieh Chiang, Li Wei Chan, Yi Ping Hung, Greg C. Lee

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Object movie refers to a set of images captured from different perspectives around a 3D object. Object movie provides a good representation of a physical object because it can provide 3D interactive viewing effect, but does not require 3D model reconstruction. In this paper, we propose an efficient approach for content-based object movie retrieval. In order to retrieve the desired object movie from the database, we first map an object movie into the sampling of a manifold in the feature space. Two different layers of feature descriptors, dense and condensed, are designed to sample the manifold for representing object movies. Based on these descriptors, we define the dissimilarity measure between the query and the target in the object movie database. The query we considered can be either an entire object movie or simply a subset of views. We further design a relevance feedback approach to improving retrieved results. Finally, some experimental results are presented to show the efficacy of our approach.

Original languageEnglish
Article number89691
JournalEurasip Journal on Advances in Signal Processing
Volume2007
DOIs
Publication statusPublished - 2007 Aug 1

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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