AIR: An Agent for Robust Image Matching and Retrieval
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2013, Vol 1, Issue 2
Abstract
This paper presents a novel scheme coined AIR (Agent for Image Recognition), acting as an agent, to oversee the image matching and retrieval processes. Firstly, neighboring keypoints within close spatial proximity are examined and used to hypothesize true keypoint matches. While this approach is robust to noise (e.g. a tree) since spatial relation is considered, missing (undetected) keypoints in one image can also be recovered resulting in more keypoint matches. Secondly, the agent is able to recognize instability of projective transformations in certain cases (e.g. non-planar scenes). The geometric approach is substituted with LIS (Longest Increasing Subsequence) approach which does not require any complex geometric transformations. The effectiveness of AIR is substantiated by an image retrieval experiment which demonstrates that it achieves a twofold increase in true matches and higher matching accuracy when compared to RANSAC homography approach.
Authors and Affiliations
Jimmy Addison Lee*| Institute for Infocomm Research, Singapore, Attila Szabó| Institute for Infocomm Research, Singapore, Yiqun Li| Institute for Infocomm Research, Singapore
Keywords
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