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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Sharif University of Technology</PublisherName>
				<JournalTitle>Scientia Iranica</JournalTitle>
				<Issn>1026-3098</Issn>
				<Volume>22</Volume>
				<Issue>6</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A novel computational model of stereo depth estimation for robotic vision systems</ArticleTitle>
<VernacularTitle>A novel computational model of stereo depth estimation for robotic vision systems</VernacularTitle>
			<FirstPage>2188</FirstPage>
			<LastPage>2197</LastPage>
			<ELocationID EIdType="pii">3768</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>K.-Y.</FirstName>
					<LastName>Chen</LastName>
<Affiliation>Department of Mechanical Engineering, Chung Yuan Christian University, 200, Chungpei Rd., Chungli District, Taoyuan City, 32023, Taiwan, R.O.C.</Affiliation>

</Author>
<Author>
					<FirstName>Ch.-H.</FirstName>
					<LastName>Chen</LastName>
<Affiliation>Department of Mechanical Engineering, Chung Yuan Christian University, 200, Chungpei Rd., Chungli District, Taoyuan City, 32023, Taiwan, R.O.C.</Affiliation>

</Author>
<Author>
					<FirstName>Ch.-Ch.</FirstName>
					<LastName>Chien</LastName>
<Affiliation>Department of Mechanical Engineering, Chung Yuan Christian University, 200, Chungpei Rd., Chungli District, Taoyuan City, 32023, Taiwan, R.O.C.</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>02</Day>
				</PubDate>
			</History>
		<Abstract>This paper presents a novel computational model of stereovision for improving the accuracy of three-dimensional data extracted from a stereo-pair image with no eect of changes in focal length. For decades, most previous studies on stereovision have focused on the establishment of stereo matching, and have made conclusions on the premise of a xed focus. In general, error in the depth estimate becomes bigger when the focus and aperture are unknown or not xed. For that reason, a three-stage framework is proposed in this paper to modify the conventional stereovision model for improving the accuracy of depth estimation. The rst stage is to modify the computational model of conventional stereovision for varifocal cameras. Then, the spacing of depth intervals in the non-uniform spacing of discrete depth levels can be altered, in particular, to be unaected by changes in focal length. Finally, by considering the ane transformation, we add the deformation coecient into the modied stereovision model for correcting three-dimensional ane deformations. Experimental results demonstrated that the depth estimation from stereo images using the proposed scheme was more accurate than conventional methods. The percentage error of most estimates fell between 0.06%-0.82%, and the error value increased from 0.02 cm to 2.21 cm within 6 m.</Abstract>
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			<Object Type="keyword">
			<Param Name="value">Stereovision</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Variable focal length</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Robotic vision</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Ane deformation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Non-uniform spacing</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://scientiairanica.sharif.edu/article_3768_e53359de85e46000c60a4604b6781492.pdf</ArchiveCopySource>
</Article>
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