<ul><li>A method for lightweight omnidirectional stereovision with fisheye images has been introduced by a robotics research team.</li><li>The method involves selecting Geometry-Informed (GI) distance candidates to enhance depth estimation accuracy and reduce computational load.</li><li>The GI candidates are adaptable to alterations in camera distances without the need for re-training, making them valuable in dynamic settings.</li><li>The findings highlight improved accuracy in estimating distances and quicker model performance using the GI candidates method.</li></ul>

Geometry-Informed Distance Candidate Selection for Adaptive Lightweight Omnidirectional Stereo…

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