Performance Tuning on Multicore Systems for Feature Matching within Image Collections Xiaoxin Tang*, Steven Mills, David Eyers, Zhiyi Huang, Kai-Cheung Leung and Minyi Guo* Department of Computer Science University of Otago, New Zealand * Department of Computer Science Shanghai Jiao Tong University, China
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Performance Tuning on Multicore Systems for Feature Matching within Image Collections
Performance Tuning on Multicore Systems for Feature Matching within Image Collections. Xiaoxin Tang*, Steven Mills, David Eyers, Zhiyi Huang , Kai-Cheung Leung and Minyi Guo * Department of Computer Science University of Otago , New Zealand * Department of Computer Science - PowerPoint PPT Presentation
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Performance Tuning on Multicore Systems for
Feature Matching within Image Collections
Xiaoxin Tang*, Steven Mills, David Eyers, Zhiyi Huang, Kai-Cheung Leung and Minyi Guo*
Department of Computer Science University of Otago, New Zealand
* Department of Computer ScienceShanghai Jiao Tong University, China
Contents
• Motivation• Our work• Evaluation• Conclusion
Contents
• Motivation• Our work• Evaluation• Conclusion
Similarity Search
• Definition:– To preprocess a database of N objects so that
given a query object, one can effectively determine its nearest neighbors in database.
• Applications:– pattern recognition, chemical similarity
analysis, and statistical classification, etc.
The problem – KNN Search
• K Nearest Neighbor Search:– Feature: an array of D elements
Conclusion• We have shown that performance tuning is
demanding on modern multicore systems.
• We have comprehensively evaluated the impact of the three factors that have an influence on large-scale image feature matching.
• We have proposed a Divide-and-Merge algorithm that can greatly improve the speedup and scalability of feature matching algorithms on multicore machines.