Visually reading the configuration of a Rubiks cube using Probabilistic Graphical Model
Sunil S Nandihalli
Identify the edges in the field of view and then correlate the sequence of frames to infer the configuration of the rubiks cube. The audience will be able to take away as to how one can correlate information from video frames to infer the kinematics of the object in the field of view
Describe an algorithm to infer the edges in a video followed by building a probabilistic graphical model to identify the color, and position of the rubiks cube.
Sunil is currently heading the datasciences effort at AppLift. During his stay there, along with his colleagues, has worked on modeling the auction mechanism and KPI prediction models. In the yester years, he has worked in building search index to enable contextual recommendations. He has also worked in meshing to enable computation simulations in the early part of his career.