Camera Constraint-Free View-Based 3-D Object Retrieval

Recently, extensive research efforts have been dedicated to view-based methods for 3-D object retrieval due to the highly discriminative property of multiviews for 3-D object representation. However, most of state-of-the-art approaches highly depend on their own camera array settings for capturing v...

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Vydané v:	IEEE transactions on image processing Ročník 21; číslo 4; s. 2269 - 2281
Hlavní autori:	Yue Gao, Jinhui Tang, Hong, Richang, Shuicheng Yan, Qionghai Dai, Naiyao Zhang, Tat-Seng Chua
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.04.2012
Predmet:	3-D object Algorithms Arrays Camera constraint-free Cameras Computational modeling Educational institutions Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Imaging, Three-Dimensional - methods Information Storage and Retrieval - methods Pattern Recognition, Automated - methods Photography - methods Reproducibility of Results retrieval Sensitivity and Specificity Signal Processing, Computer-Assisted Solid modeling Subtraction Technique Three dimensional displays view-based
ISSN:	1057-7149, 1941-0042, 1941-0042
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Abstract	Recently, extensive research efforts have been dedicated to view-based methods for 3-D object retrieval due to the highly discriminative property of multiviews for 3-D object representation. However, most of state-of-the-art approaches highly depend on their own camera array settings for capturing views of 3-D objects. In order to move toward a general framework for 3-D object retrieval without the limitation of camera array restriction, a camera constraint-free view-based (CCFV) 3-D object retrieval algorithm is proposed in this paper. In this framework, each object is represented by a free set of views, which means that these views can be captured from any direction without camera constraint. For each query object, we first cluster all query views to generate the view clusters, which are then used to build the query models. For a more accurate 3-D object comparison, a positive matching model and a negative matching model are individually trained using positive and negative matched samples, respectively. The CCFV model is generated on the basis of the query Gaussian models by combining the positive matching model and the negative matching model. The CCFV removes the constraint of static camera array settings for view capturing and can be applied to any view-based 3-D object database. We conduct experiments on the National Taiwan University 3-D model database and the ETH 3-D object database. Experimental results show that the proposed scheme can achieve better performance than state-of-the-art methods.
AbstractList	Recently, extensive research efforts have been dedicated to view-based methods for 3-D object retrieval due to the highly discriminative property of multiviews for 3-D object representation. However, most of state-of-the-art approaches highly depend on their own camera array settings for capturing views of 3-D objects. In order to move toward a general framework for 3-D object retrieval without the limitation of camera array restriction, a camera constraint-free view-based (CCFV) 3-D object retrieval algorithm is proposed in this paper. In this framework, each object is represented by a free set of views, which means that these views can be captured from any direction without camera constraint. For each query object, we first cluster all query views to generate the view clusters, which are then used to build the query models. For a more accurate 3-D object comparison, a positive matching model and a negative matching model are individually trained using positive and negative matched samples, respectively. The CCFV model is generated on the basis of the query Gaussian models by combining the positive matching model and the negative matching model. The CCFV removes the constraint of static camera array settings for view capturing and can be applied to any view-based 3-D object database. We conduct experiments on the National Taiwan University 3-D model database and the ETH 3-D object database. Experimental results show that the proposed scheme can achieve better performance than state-of-the-art methods. Recently, extensive research efforts have been dedicated to view-based methods for 3-D object retrieval due to the highly discriminative property of multiviews for 3-D object representation. However, most of state-of-the-art approaches highly depend on their own camera array settings for capturing views of 3-D objects. In order to move toward a general framework for 3-D object retrieval without the limitation of camera array restriction, a camera constraint-free view-based (CCFV) 3-D object retrieval algorithm is proposed in this paper. In this framework, each object is represented by a free set of views, which means that these views can be captured from any direction without camera constraint. For each query object, we first cluster all query views to generate the view clusters, which are then used to build the query models. For a more accurate 3-D object comparison, a positive matching model and a negative matching model are individually trained using positive and negative matched samples, respectively. The CCFV model is generated on the basis of the query Gaussian models by combining the positive matching model and the negative matching model. The CCFV removes the constraint of static camera array settings for view capturing and can be applied to any view-based 3-D object database. We conduct experiments on the National Taiwan University 3-D model database and the ETH 3-D object database. Experimental results show that the proposed scheme can achieve better performance than state-of-the-art methods.Recently, extensive research efforts have been dedicated to view-based methods for 3-D object retrieval due to the highly discriminative property of multiviews for 3-D object representation. However, most of state-of-the-art approaches highly depend on their own camera array settings for capturing views of 3-D objects. In order to move toward a general framework for 3-D object retrieval without the limitation of camera array restriction, a camera constraint-free view-based (CCFV) 3-D object retrieval algorithm is proposed in this paper. In this framework, each object is represented by a free set of views, which means that these views can be captured from any direction without camera constraint. For each query object, we first cluster all query views to generate the view clusters, which are then used to build the query models. For a more accurate 3-D object comparison, a positive matching model and a negative matching model are individually trained using positive and negative matched samples, respectively. The CCFV model is generated on the basis of the query Gaussian models by combining the positive matching model and the negative matching model. The CCFV removes the constraint of static camera array settings for view capturing and can be applied to any view-based 3-D object database. We conduct experiments on the National Taiwan University 3-D model database and the ETH 3-D object database. Experimental results show that the proposed scheme can achieve better performance than state-of-the-art methods.
Author	Hong, Richang Tat-Seng Chua Jinhui Tang Shuicheng Yan Naiyao Zhang Qionghai Dai Yue Gao
Author_xml	– sequence: 1 surname: Yue Gao fullname: Yue Gao email: gaoyue08@mails.tsinghua.edu.cn organization: Dept. of Autom., Tsinghua Univ., Beijing, China – sequence: 2 surname: Jinhui Tang fullname: Jinhui Tang email: jinhui-tang@mail.njust.edu.cn organization: Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China – sequence: 3 givenname: Richang surname: Hong fullname: Hong, Richang email: hongrc.hfut@gmail.com organization: Sch. of Comput. & Inf. Sci., Hefei Univ. of Technol., Hefei, China – sequence: 4 surname: Shuicheng Yan fullname: Shuicheng Yan email: eleyans@nus.edu.sg organization: Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore – sequence: 5 surname: Qionghai Dai fullname: Qionghai Dai email: qhdai@tsinghua.edu.cn organization: Dept. of Autom., Tsinghua Univ., Beijing, China – sequence: 6 surname: Naiyao Zhang fullname: Naiyao Zhang email: zlh@tsinghua.edu.cn organization: Dept. of Autom., Tsinghua Univ., Beijing, China – sequence: 7 surname: Tat-Seng Chua fullname: Tat-Seng Chua email: chuats@comp.nus.edu.sg organization: Sch. of Comput., Nat. Univ. of Singapore, Singapore, Singapore
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SubjectTerms	3-D object Algorithms Arrays Camera constraint-free Cameras Computational modeling Educational institutions Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Imaging, Three-Dimensional - methods Information Storage and Retrieval - methods Pattern Recognition, Automated - methods Photography - methods Reproducibility of Results retrieval Sensitivity and Specificity Signal Processing, Computer-Assisted Solid modeling Subtraction Technique Three dimensional displays view-based
Title	Camera Constraint-Free View-Based 3-D Object Retrieval
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