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dc.contributor.authorSeabright, Matthewen_NZ
dc.contributor.authorStreeter, Leeen_NZ
dc.contributor.authorCree, Michael J.en_NZ
dc.contributor.authorDuke, Mikeen_NZ
dc.contributor.authorTighe, Rachelen_NZ
dc.coverage.spatialAuckland, New Zealanden_NZ
dc.date.accessioned2019-04-10T00:18:28Z
dc.date.available2018en_NZ
dc.date.available2019-04-10T00:18:28Z
dc.date.issued2018en_NZ
dc.identifier.citationSeabright, M., Streeter, L. V., Cree, M. J., Duke, M., & Tighe, R. (2018). Simple stereo matching algorithm for localising keypoints in a restricted search space. Presented at the International Conference on Image and Vision Computing New Zealand (IVCNZ), Auckland, New Zealand: IEEE. https://doi.org/10.1109/IVCNZ.2018.8634791en
dc.identifier.urihttps://hdl.handle.net/10289/12453
dc.description.abstractModern stereo matching algorithms generally rely on matching image features such as colour and texture to find corresponding matches between images. They can provide very good results but be very computationally intensive. However, in cases where the objects to be localised lie approximately on a known plane, a much simpler algorithm can be applied. One such case is localising kiwifruit in modern orchards, as the plants are trained to grow in a planar structure known as a pergola. The proposed algorithm uses tight distance limits (based on orchard geometry) to reduce the search space for matching fruit to a small window. For the majority of kiwifruit, the search window is small enough to contain only one fruit in the adjacent image, giving only a single solution. In cases where there are tightly grouped fruit or false positive fruit detections adjacent to true positive fruit detections, there can be multiple potential matching solutions. To solve these, each potential solution is evaluated based on how closely it conforms to the mean object distance from camera and a solution is selected. On real world test data containing 121 image pairs, the algorithm has a 99.2 % true positive rate. Computation time was 1.97 ms per image pair.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherIEEEen_NZ
dc.rights© 2018 IEEE. This is the author's version of the work. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
dc.sourceInternational Conference on Image and Vision Computing New Zealand (IVCNZ)en_NZ
dc.titleSimple stereo matching algorithm for localising keypoints in a restricted search spaceen_NZ
dc.typeConference Contribution
dc.identifier.doi10.1109/IVCNZ.2018.8634791en_NZ
pubs.elements-id235911
pubs.finish-date2018-12-21en_NZ
pubs.start-date2018-12-19en_NZ


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