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Graph."],"published-print":{"date-parts":[[2010,12]]},"abstract":"<jats:p>\n            Image resizing can be achieved more effectively if we have a better understanding of the image semantics. In this paper, we analyze the\n            <jats:italic>translational symmetry<\/jats:italic>\n            , which exists in many real-world images. By detecting the symmetric lattice in an image, we can\n            <jats:italic>summarize<\/jats:italic>\n            , instead of only distorting or cropping, the image content. This opens a new space for image resizing that allows us to manipulate, not only image pixels, but also the semantic\n            <jats:italic>cells<\/jats:italic>\n            in the lattice. As a general image contains both symmetry &amp; non-symmetry regions and their natures are different, we propose to resize symmetry regions by summarization and non-symmetry region by warping. The difference in resizing strategy induces discontinuity at their shared boundary. We demonstrate how to reduce the artifact. To achieve practical resizing applications for general images, we developed a fast symmetry detection method that can detect multiple disjoint symmetry regions, even when the lattices are curved and perspectively viewed. Comparisons to state-of-the-art resizing techniques and a user study were conducted to validate the proposed method. Convincing visual results are shown to demonstrate its effectiveness.\n          <\/jats:p>","DOI":"10.1145\/1882261.1866185","type":"journal-article","created":{"date-parts":[[2010,12,1]],"date-time":"2010-12-01T20:18:10Z","timestamp":1291234690000},"page":"1-10","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":47,"title":["Resizing by symmetry-summarization"],"prefix":"10.1145","volume":"29","author":[{"given":"Huisi","family":"Wu","sequence":"first","affiliation":[{"name":"The Chinese University of Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu-Shuen","family":"Wang","sequence":"additional","affiliation":[{"name":"National Cheng Kung University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kun-Chuan","family":"Feng","sequence":"additional","affiliation":[{"name":"National Cheng Kung University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tien-Tsin","family":"Wong","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tong-Yee","family":"Lee","sequence":"additional","affiliation":[{"name":"National Cheng Kung University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pheng-Ann","family":"Heng","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2010,12,15]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"crossref","unstructured":"Ahuja N. and Todorovic S. 2007. 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In ECCV (1) 546--555.   Leung T. K. and Malik J. 1996. Detecting localizing and grouping repeated scene elements from an image. 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