Visual Utility – A Framework for Focusing Computer Vision Algorithms
Event Location: NSH 3305Abstract: The real world is a rich environment, fraught with complexity. To be robust in this complex environment, computer Vision algorithms that operate in Unstructured Environments (VUE) tend to use large amounts of data or complex modeling. Unfortunately, these algorithms also require significant computational resources. In this thesis, we examine a visual [...]
OpenDR: An Approximate Differentiable Renderer
Event Location: NSH 1507Bio: Matthew Loper is a research engineer at Industrial Light and Magic, and a PhD candidate at the University of Tuebingen. He received his ScM from Brown University in 2008. His current research interests include differentiable rendering and statistical body shape modeling.Abstract: Inverse graphics attempts to take sensor data and infer 3D [...]
Context-sensitive Dynamic Ordinal Regression for Human Facial Behaviour Analysis
Event Location: NSH 1507Bio: Ognjen Rudovic received a PhD from Department of Computing, Imperial College London, UK, in 2014, an MSc degree in Computer Vision and Artificial Intelligence from Computer Vision Centre (CVC), Barcelona, Spain, in 2008, and BSc in Automatic Control Theory from Electrical Engineering Dept., University Of Belgrade, Serbia, in 2007. He is [...]
Multimodal Machine Learning: Modeling Human Communication Dynamics
Event Location: NSH 1305Bio: Louis-Philippe Morency is Assistant Professor in the Language Technology Institute at the Carnegie Mellon University where he leads the Multimodal Communication and Machine Learning Laboratory (MultiComp Lab). He received his Ph.D. and Master degrees from MIT Computer Science and Artificial Intelligence Laboratory. In 2008, Dr. Morency was selected as one of [...]
Towards Large-scale Video Understanding
Event Location: NSH 1507Bio: Chen Sun is a Ph.D. candidate in the Computer Vision group at University of Southern California, advised by Prof. Ram Nevatia. His research interest includes Computer Vision and Machine Learning, with a focus on large-scale video understanding. Chen got his bachelor degree in Computer Science at Tsinghua University, Beijing. He has [...]
Learning optimal seeds for diffusion based salient object detection
Event Location: NSH 1507Bio: Vijay Mahadevan is Research Scientist at Yahoo Labs in Sunnyvale, CA. He received the Ph.D degree in Electrical Engineering from UC San Diego. He also has an M.S. from Rensselaer, and a B.Tech from Indian Institute of Technology, Madras. His interests are in the areas of computer vision, machine learning and [...]
Crowds and Robots: Leveraging the Web to Advance Robot Autonomy
Event Location: NSH 1305Bio: Sonia Chernova is the Catherine M. and James E. Allchin Early-Career Assistant Professor in the School of Interactive Computing, and the director of the Robot Autonomy and Interactive Learning (RAIL) lab. Her research interests span robotics, interactive machine learning, adjustable autonomy, human computation and human-robot interaction. Dr. Chernova received her Ph.D. [...]
Using Motion to Understand Objects in the Real World
Event Location: NSH 1507Bio: David Held is a Computer Science Ph.D. student at Stanford doing research at the intersection of robotics, computer vision, and machine learning. He is co-advised by Sebastian Thrun and Silvio Savarese. David has also interned at Google, working on the self-driving car project. Before Stanford, he worked as a software developer [...]
A Reflex-based Neuromuscular Control Model of Human Locomotion
Event Location: GHC 4405Abstract: The neural controls of human and animal locomotion have been studied over centuries. However, much of our knowledge about the locomotion control of complex species, especially humans, still relies on extrapolating from what is known in simpler animals. One barrier for better understanding the control of human locomotion is that we [...]