ADR Awareness Centre

Deep Convolutional Generative Adversarial Networks (DCGAN) have been used to generate highly compelling pictures or videos, such as manipulated facial animations, interior and outdoor images, videos.

This lecture overviews  digital images, image processing and image analysis. 1D signals, 2D signals (images), 3D signals (videos, medical volumes) are presented. Multichannel images, e.g., color and multispectral images come next.

This lecture overviews Computational Geometry that has many applications in Computer Graphics, Robotics, Geographic Information Systems, CAD/CAM.

This lecture overviews Mathematical Morphology  that has many applications in digital image processing, analysis and computer vision.

This lecture overviews Shape Description that has many applications in object recognition and image compression. It covers the following topics in detail: Chain Codes. Polygonal Contour Approximations. Fourier Descriptors. Quadtrees.

This lecture overviews 2D Image Registration that has many applications in photography, computer vision, and medical imaging.

This lecture overviews digital images and 2D Computer Vision (image analysis).

This lecture overviews Computational Cinematography that has many applications in filming, notably in drone cinematography.

This lecture overviews  object pose estimation   that has many applications in Human-Robotic Interaction (HRI), Robotics and Augmented Reality.

This lecture overviews 3D Object Localization that has many applications in robotics and autonomous systems.

This lecture overviews Neural SLAM   that has many applications in robotic and autonomous vehicle localization and mapping.

The lecture includes the essential knowledge about how we obtain/get 2D and/or 3D maps that robots/drones need, taking measurements that allow them to perceive their environment with appropriate sensors.