The joint image variety
Event Location: NSH 1507Bio: Matthew Trager is a second year PhD student at Inria/ENS Paris. In 2014 he received a master's in applied mathematics (Degree in Mathematics, Machine Learning and Computer Vision "MVA") from École Normale Supérieure de Cachan. Previously, he received a master's in pure mathematics from Scuola Normale Superiore in Pisa. His research [...]
My Adventured with Bayes: In search of optimal solutions in machine learning, computer vision and beyond
Event Location: NSH 1507Bio: Aleix M. Martinez is a Professor in the Department of Electrical and Computer Engineering at The Ohio State University (OSU), where he is the founder and director of the Computational Biology and Cognitive Science Lab. He is also affiliated with the Department of Biomedical Engineering and to the Center for Cognitive [...]
Supervised Descent Method
Event Location: GHC 8102Abstract: In this dissertation, we focus on solving NLS problems using a supervised approach. In particular, we developed a Supervised Descent Method (SDM), performed thorough theoretical analysis, and demonstrated its effectiveness on optimizing analytic functions, and four other real-world applications: Inverse Kinematics, Rigid Tracking, Face Alignment (frontal and multi-view), and 3D Object [...]
Versatility in Robotic Manipulation: the Long Road to Everywhere
Event Location: NSH 1305Bio: Matei Ciocarlie is an assistant professor of Mechanical Engineering and affiliate assistant professor of Computer Science at Columbia University. His main interest is in reliable robotic manipulation in unstructured, human environments, focusing on areas such as novel hand designs and control, autonomous and Human-in-the-Loop mobile manipulation, shared autonomy, teleoperation, and assistive [...]
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 [...]