As part of the Dept. of Computer Science Interdisciplinary Seminar Series, Ross Finman (Marine Robotics Group, MIT) will present a seminar at 11am Thursday, Oct 3rd, entitled, "Lifelong Object Segmentation from Change Detection in Dense RGB-D Maps ". An abstract for the seminar is given below.
The seminar will be held in the Computer Science Seminar Room (CSR), on the ground floor of the Department of Computer Science.
Title: Lifelong Object Segmentation from Change Detection in Dense RGB-D Maps
Robots have finally escaped from industrial workplaces and are making their way into our homes, offices, and public spaces. In order to realize the dream of robot assistants performing tasks together with humans, we need to provide them with the capability of understanding complex, unstructured, large-scale environments and the objects within them. Ideally this understanding is developed autonomously as not to burden a user. In this talk we present our work on enabling robot systems to discover, segment, and detect objects in the context of the environment the systems are working in. Having robots learn objects from their environment instead of from large databases provides a more adaptive system to function in the complex real world. Specifically, we use motion cues in dense RGB-D maps to discover objects in their environment, thus learning the objects that are most frequently used. We then discuss how to use these learned objects to optimize multiple scene segmentations in order to segment the object on future traverses. Lastly, we will discuss current work on segmenting maps in an efficient, real-time framework to detect objects on mobile robotic platforms.
Ross Finman is a Ph.D. Student in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. His research is focused on the intersection of computer vision and robotic mapping applications by using theory developed for the former in the new data domain of the latter.