Kostas Daniilidis




Kostas' research interests are in computer vision and robotic perception. His research addresses challenges in the perception of motion and space, as applied in navigation and manipulation. Kostas' research gives solutions to perceptual tasks such as semantic localization, perception of self-motion, and 3-D object recognition.

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E.g., 2017-09-26
E.g., 2017-09-26
E.g., 2017-09-26
Oct 2nd 2017

How can robots perceive the world and their own movements so that they accomplish navigation and manipulation tasks? In this module, we will study how images and videos acquired by cameras mounted on robots are transformed into representations like features and optical flow. Such 2D representations allow us then to extract 3D information about where the camera is and in which direction the robot moves. You will come to understand how grasping objects is facilitated by the computation of 3D posing of objects and navigation can be accomplished by visual odometry and landmark-based localization.

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Learn how to design robot vision systems that avoid collisions, safely work with humans and understand their environment. How do robots “see”, respond to and learn from their interactions with the world around them? This is the fascinating field of visual intelligence and machine learning. Visual intelligence allows a robot to “sense” and “recognize” the surrounding environment. It also enables a robot to “learn” from the memory of past experiences by extracting patterns in visual signals.

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