Science Daily May 26, 2022
Many modern imaging sensors must obtain multiple looks or “views” of a target at different orientations to automatically classify it with high confidence. Therefore, when tasked with classifying many targets, a mobile sensor may need to travel a long distance to change its position and orientation relative to every target, resulting in costly and time-consuming operations. A team of researchers in the US (Cornell University, Naval Surface Warfare Center) has developed a new approach, referred to as informative multiview planning (IMVP) that simultaneously determines the most informative sequence of views and the shortest path between them. They demonstrated their method in an underwater multitarget classification problem in which a side scan sonar installed on an unmanned underwater vehicle had to classify all targets in the shortest amount of time. Simulation and experimental results show that IMVP can achieve the same, or better, classification performance in half the time of existing multiview path planning methods. IMVP significantly improves classification efficiency, classification confidence level, as well as performance robustness… read more. Open Access TECHNICAL ARTICLE