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                <identifier>ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:1:6361</identifier>
                <datestamp>2018-11-17T13:54:38Z</datestamp>
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                    <dim:field mdschema="dc" element="title" lang="en">Approximate convex decomposition for 2D shapes based on visibility range</dim:field>
                    <dim:field mdschema="dc" element="date" qualifier="issued">2016</dim:field>
                    <dim:field mdschema="dc" element="identifier" qualifier="uri">http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/1/6361</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="id:23998" confidence="-1">Z. Li</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="id:23999" confidence="-1">W. Qu</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="id:24000" confidence="-1">H. Qi</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="orcid::0000-0001-6279-2988" confidence="-1">M. Stojmenović</dim:field>
                    <dim:field mdschema="dc" element="description" qualifier="abstract">Organizing shapes by convex parts is a fundamental procedure for many shape-related applications. However, convexity is sensitive to noise and shape variations. Recent publications in the field concentrated on decomposing shapes into near-convex parts. Although a variety of methods have been presented, there is still a need for a robust and versatile method, especially when a shape possesses long curved branches such as a lizard with a long curved tail. It is difficult to capture the tail as a whole part because its concavity is too high based on classic measures. To address this issue, we propose a `Visibility Range&amp;apos;, novel shape signature in this paper. Visibility range reaches low values for points in concave regions and high values in convex regions. Moreover, a novel concavity measure based on visibility range is presented. Compared to previous measures, the novel measure describes long curved branches better. With these, a simple but effective shape decomposition algorithm is designed. The decomposition is formulated as a problem of detecting points with extreme visibility range in a visibility matrix. Extensive experiments have been done on shapes with various kinds of near-convex parts, demonstrating that the proposed method is more robust and effective than the state-of-art methods based on other concave-convex features.</dim:field>
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                    <dim:field mdschema="dc" element="identifier" qualifier="doi">10.1109/ICME.2016.7552991</dim:field>
                    <dim:field mdschema="dc" element="source">Multimedia and Expo (ICME), 2016 IEEE International Conference on</dim:field>
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