Journal
IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 25, Issue 12, Pages 5814-5827Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2016.2614132
Keywords
3D object; retrieval; multi-view; topic model
Funding
- National Basic Research Program [2013CB336500]
- National High-Tech Development Program [2014AA015104]
- National Nature Science Foundation of China [61472116]
- Anhui Fund for Distinguished Young Scholars [1508085J04]
- Australian Research Council [DP-140102164, FT-130101457, LE-140100061]
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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.
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