Video Compression for Recognition & Video Recognition for Compression
Abstract: Training robust deep video representations has proven to be much more challenging than learning deep image representations. One reason is: videos are huge and highly redundant. The 'true' and interesting signal often drowns in too much irrelevant data. In the first part of the talk, I will show how to train a deep network [...]
Multimodal Computational Behavior Understanding
Emotions influence our lives. Observational methods of measuring affective behavior have yielded critical insights, but a persistent barrier to their wide application is that they are labor-intensive to learn and to use. An automated system that can quantify and synthesize human affective behavior in real-world environments would be a transformational tool for research and for [...]
Learning Robot Manipulation Skills through Experience and Generalization
Abstract: In the future, robots could be used to take care of the elderly, perform household chores, and assist in hazardous situations. However, such applications require robots to manipulate objects in unstructured and everyday environments. Hence, in order to perform a wide range of tasks, robots will need to learn manipulation skills that generalize between [...]
Fully Autonomous Drones for Wind Power Turbine Inspection
Abstract: The wind energy industry is growing rapidly. In the U.S. alone, the wind industry invested more than $11 billion in new plants in 2017 and added more than 7,000 megawatts of new capacity, representing 25% of all electric capacity added. One of the biggest challenges to growth remains the high costs of constructing wind [...]
Signal to Symbol (via Skills)
Abstract: While recent years have seen dramatic progress in the development of affordable, general-purpose robot hardware, the capabilities of that hardware far exceed our ability to write software to adequately control. The key challenge here is one of abstraction: generally capable behavior requires high-level reasoning and planning, but perception and actuation must ultimately be performed [...]
Carnegie Mellon University
Sparse and Dense Methods for Underwater Localization and Mapping with Imaging Sonar
Abstract: Imaging sonars have been used for a variety of tasks geared towards increasing autonomy of underwater vehicles: image registration and mosaicing, vehicle localization, object recognition, mapping, and path planning, to name a few. However, the complexity of the image formation has led many algorithms to make the restrictive assumption that the scene geometry is [...]
Carnegie Mellon University
Deep Interpretable Non-rigid Structure from Motion
Abstract: Current non-rigid structure from motion (NRSfM) algorithms are limited with respect to: (i) the number of images, and (ii) the type of shape variability they can handle. This has hampered the practical utility of NRSfM for many applications within vision. Deep Neural Networks (DNNs) are an obvious candidate to help with such issue. However, [...]
RI Faculty Social All Robotics Institute faculty are invited to attend this informal team-building business/social event
All Robotics Institute faculty are invited to attend this informal team-building business/social event. Our November Robotics Institute Faculty Social will be hosted by Martial Hebert in NSH 4305, from 3:00 to 4:00pm.