University of Western Australia
3D Computer Vision for Future Robots
Robotics has made significant progress in cases of structured and constrained environments, e.g., manufacturing. However, it is still in its infancy when it comes to applications in unstructured and unconstrained situations e.g., social environments. In some respects, such as speed, strength and accuracy, robots have superior capacities compared to humans but that is not the case for person/object recognition, language, manual dexterity, and social interaction and understanding capabilities.
Developing a computer vision system with Human visual recognition capabilities has been a very big challenge. It has been hindered mainly by: (i) the non-availability of 3D sensors (with the capabilities of the human eye) which are able to simultaneously capture appearance (colour and texture), surface shapes of objects while in motion, and (ii) the non-availability of algorithms to process this information in real-time. Recently, several affordable 3D sensors appeared in the market which is resulting in the development of practical 3D systems. Examples include 3D object and 3D face recognition for biometric applications, as well as the development of home robotic platforms to assist the elderly with mild cognitive impairment.
The objective of the talk will be to describe few 3D computer vision projects and tools used towards the development of a platform for assistive robotics in messy living environments. Various systems with applications and their motivations will be described including 3D object recognition, 3D face/ear biometrics, grasping of unknown objects, and systems to estimate the 3D pose of a person.
Mohammed Bennamoun is Winthrop Professor in the Department of Computer Science and Software Engineering at the University of Western Australia (UWA) and is a researcher in computer vision, machine/deep learning, robotics, and signal/speech processing. He has published 4 books (available on Amazon), 1 edited book, 1 Encyclopedia article, 14 book chapters, 200+ journal papers, 270+ conference publications, 16 invited and keynote publications. His h-index is 71 and his number of citations is 23,200+ (Google Scholar). He was awarded 70+ competitive research grants, from the Australian Research Council, and numerous other Government, UWA and industry Research Grants. He successfully supervised 30+ PhD students to completion. He won the Best Supervisor of the Year Award at Queensland University of Technology (1998) and received award for research supervision at UWA (2008 and 2016) and Vice-Chancellor Award for mentorship (2016). He delivered conference tutorials at major conferences, including IEEE CVPR 2016, Interspeech 2014, IEEE ICASSP, and ECCV. He was also invited to give a Tutorial at an International Summer School on Deep Learning (DeepLearn 2017).