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- W2775404703 abstract "This paper describes an algorithm for visually detecting crop stalks in-situ. Field-based crop stalk detection is a challenging computer vision problem due to occlusion by leaves, similarity of color and texture between stalks and surrounding foliage, and high stalk density within rows. Detecting stalks for grasping adds further challenges such as computation time and computing hardware. The proposed algorithm utilizes multiple stereo images taken from an unmanned ground vehicle and exploits geometric features specific to stalks such as vertical continuity, height, and the direction of surface normals. The described hardware and software pipeline is capable of detecting stalks for a manipulator grasp in approximately 12 seconds, and preliminary results show that hardware improvements can reduce detection time to 4 seconds. The algorithm is tested on 378 point clouds generated from 916 images of Sorghum bicolor, a grain crop. Performance is evaluated according to two methods, demonstrating precision greater than 93%." @default.
- W2775404703 created "2017-12-22" @default.
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- W2775404703 date "2017-09-01" @default.
- W2775404703 modified "2023-09-26" @default.
- W2775404703 title "Online detection of occluded plant stalks for manipulation" @default.
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- W2775404703 doi "https://doi.org/10.1109/iros.2017.8206404" @default.
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