Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/615343
Title: Multi-View Object Retrieval via Multi-Scale Topic Models
Authors: Richang Hong;Zhenzhen Hu;Ruxin Wang;Meng Wang;Dacheng Tao
subject: retrieval|multi-view|topic model|3D object
Year: 2016
Publisher: IEEE
Abstract: The increasing number of 3D objects in various applications has increased the requirement for effective and efficient 3D object retrieval methods, which attracted extensive research efforts in recent years. Existing works mainly focus on how to extract features and conduct object matching. With the increasing applications, 3D objects come from different areas. In such circumstances, how to conduct object retrieval becomes more important. To address this issue, we propose a multi-view object retrieval method using multi-scale topic models in this paper. In our method, multiple views are first extracted from each object, and then the dense visual features are extracted to represent each view. To represent the 3D object, multi-scale topic models are employed to extract the hidden relationship among these features with respect to varied topic numbers in the topic model. In this way, each object can be represented by a set of bag of topics. To compare the objects, we first conduct topic clustering for the basic topics from two data sets, and then generate the common topic dictionary for new representation. Then, the two objects can be aligned to the same common feature space for comparison. To evaluate the performance of the proposed method, experiments are conducted on two data sets. The 3D object retrieval experimental results and comparison with existing methods demonstrate the effectiveness of the proposed method.
URI: http://localhost/handle/Hannan/148358
http://localhost/handle/Hannan/615343
ISSN: 1057-7149
1941-0042
volume: 25
issue: 12
Appears in Collections:2016

Files in This Item:
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Title: Multi-View Object Retrieval via Multi-Scale Topic Models
Authors: Richang Hong;Zhenzhen Hu;Ruxin Wang;Meng Wang;Dacheng Tao
subject: retrieval|multi-view|topic model|3D object
Year: 2016
Publisher: IEEE
Abstract: The increasing number of 3D objects in various applications has increased the requirement for effective and efficient 3D object retrieval methods, which attracted extensive research efforts in recent years. Existing works mainly focus on how to extract features and conduct object matching. With the increasing applications, 3D objects come from different areas. In such circumstances, how to conduct object retrieval becomes more important. To address this issue, we propose a multi-view object retrieval method using multi-scale topic models in this paper. In our method, multiple views are first extracted from each object, and then the dense visual features are extracted to represent each view. To represent the 3D object, multi-scale topic models are employed to extract the hidden relationship among these features with respect to varied topic numbers in the topic model. In this way, each object can be represented by a set of bag of topics. To compare the objects, we first conduct topic clustering for the basic topics from two data sets, and then generate the common topic dictionary for new representation. Then, the two objects can be aligned to the same common feature space for comparison. To evaluate the performance of the proposed method, experiments are conducted on two data sets. The 3D object retrieval experimental results and comparison with existing methods demonstrate the effectiveness of the proposed method.
URI: http://localhost/handle/Hannan/148358
http://localhost/handle/Hannan/615343
ISSN: 1057-7149
1941-0042
volume: 25
issue: 12
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7577725.pdf2.62 MBAdobe PDFThumbnail
Preview File
Title: Multi-View Object Retrieval via Multi-Scale Topic Models
Authors: Richang Hong;Zhenzhen Hu;Ruxin Wang;Meng Wang;Dacheng Tao
subject: retrieval|multi-view|topic model|3D object
Year: 2016
Publisher: IEEE
Abstract: The increasing number of 3D objects in various applications has increased the requirement for effective and efficient 3D object retrieval methods, which attracted extensive research efforts in recent years. Existing works mainly focus on how to extract features and conduct object matching. With the increasing applications, 3D objects come from different areas. In such circumstances, how to conduct object retrieval becomes more important. To address this issue, we propose a multi-view object retrieval method using multi-scale topic models in this paper. In our method, multiple views are first extracted from each object, and then the dense visual features are extracted to represent each view. To represent the 3D object, multi-scale topic models are employed to extract the hidden relationship among these features with respect to varied topic numbers in the topic model. In this way, each object can be represented by a set of bag of topics. To compare the objects, we first conduct topic clustering for the basic topics from two data sets, and then generate the common topic dictionary for new representation. Then, the two objects can be aligned to the same common feature space for comparison. To evaluate the performance of the proposed method, experiments are conducted on two data sets. The 3D object retrieval experimental results and comparison with existing methods demonstrate the effectiveness of the proposed method.
URI: http://localhost/handle/Hannan/148358
http://localhost/handle/Hannan/615343
ISSN: 1057-7149
1941-0042
volume: 25
issue: 12
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7577725.pdf2.62 MBAdobe PDFThumbnail
Preview File