Chiang, Cheng-ChiehCheng-ChiehChiangChan, Li-WeiLi-WeiChanYI-PING HUNGLee, Greg C.Greg C.Lee2009-04-292018-07-052009-04-292018-07-05200716876172http://ntur.lib.ntu.edu.tw//handle/246246/154594https://www.scopus.com/inward/record.uri?eid=2-s2.0-34547174266&doi=10.1155%2f2007%2f89691&partnerID=40&md5=5bd5c8539de8c951735eb0b258c03c00Object 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.application/pdf1609609 bytesapplication/pdfen-USContent based retrieval; Database systems; Feedback control; Interactive computer graphics; Mathematical models; Feature space; Movie database; Object movie retrieval; Object recognitionjournal article10.1155/2007/896912-s2.0-34547174266http://ntur.lib.ntu.edu.tw/bitstream/246246/154594/1/25.pdf