MIT News  June 19, 2019
State-of-the-art algorithms can sift the bad associations from the good once features have been matched, but it is very slow. With a technique developed by researchers at MIT a robot can see the object through all this clutter and accurately pick out an object, such as a small animal, that is otherwise obscured within a dense cloud of dots, within seconds of receiving the visual data. Their technique prunes away outliers in polynomial time even for increasingly dense clouds of dots. The technique can thus quickly and accurately identify objects hidden in cluttered scenes. They tested their algorithm by identifying three objects hidden in point clouds of increasing density. They were also able to identify objects in real-life scenes, including a living room, in which the algorithm was able to spot a cereal box and a baseball hat…read more. Open Access TECHNICAL ARTICLE
The MIT-developed technique quickly and smoothly matches objects to those hidden in dense point clouds (left), versus existing techniques (right) that produce incorrect, disjointed matches. Gif: Courtesy of the researchers