JRM Vol.28 No.2 pp. 234-241
doi: 10.20965/jrm.2016.p0234


Image Correspondence Based on Interest Point Correlation in Difference Streams: Method and Applications to Mobile Robot Localization

Helio Perroni Filho and Akihisa Ohya

Intelligent Robot Laboratory, University of Tsukuba
1-1-1 Tennodai, Tsukuba 305-8573, Japan

October 5, 2015
March 3, 2016
April 20, 2016
illumination invariance, place recognition, similarity measure, teaching and playback, visual localization
Visual recognition of previously visited places is a basic cognitive skill for a wide variety of living beings, including humans. This requires a method to extract relevant cues from visual input and successfully match them to memories of known locations, disregarding environmental variations such as lighting changes, viewer pose differences, moving objects and scene occlusion. Interest point correlation is a visual place recognition method inspired by results from neuroscience and psychology; specifically, it addresses those challenges by converting raw visual inputs to a low-variance representation, selecting regions-of-interest for representation matching, and identifying consistent matching trends. Real-world experiments employing a mobile robot demonstrate that interest point correlation is robust to visual changes, suggesting its founding principles are sound.
Similarity map between image sequences

Similarity map between image sequences

Cite this article as:
H. Filho and A. Ohya, “Image Correspondence Based on Interest Point Correlation in Difference Streams: Method and Applications to Mobile Robot Localization,” J. Robot. Mechatron., Vol.28 No.2, pp. 234-241, 2016.
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