CAREER: Geometric and Appearance Based Methods for Model Acquisition

George Mason University, Fairfax VA

Investigators

Abstract

The objective the proposal is to create a research environment and develop a curriculum dedicated to studying and developing prototypes of seeing systems. The emphasis will be on the fundamental issue of capturing representations of objects and environments by means of visual sensing. Goals include enhancing autonomy of robotic agents, empowering humans with additional capabilities and advancing the level of human and robot interaction. The proposed adaptive representations will capture both the geometry and the appearance of the environment at various levels of detail and will be acquired robustly by properly exploiting the context and task related constraints. The two essential properties of this visual system that distinguish our approach from previously existing methods is (1) its continuous operation in extended dynamic 3D environments and (2) its capability to adapt depending on the environment and task at hand. The intellectual merit of the proposed research will be in (1) advancing the state of the art in on-line methods for estimation of camera motion and scene structure; (2) unique learning of appearance based representations of objects and environments from a continuous video stream and (3) in the integration of the acquired models in the context of visually guided tasks. The broad impact includes advancing the understanding of biological systems, providing important guidance in building artificial systems, and together with new technological trends, will give rise to novel applications. The developed capabilities will enable more complex robotic tasks in less structured environments and advance human robot interaction -- features that are critical for deployment of (humanoid) robotic agents in service. They can also augment human navigation and planning capabilities and potentially affect the way we live and age.