News & Events

141 Events and Talks were found.


  •  TALK   Nonparametric Bayesian Latent Variable Models
    Date & Time: Friday, July 27, 2012; 12:00 PM
    Speaker: Mingyuan Zhou, Duke University
    MERL Host: Dehong Liu
    Brief
    • Bayesian nonparametrics, using stochastic processes as prior distributions, is a relatively young and rapidly growing research area in statistics and machine learning. In this talk, we first briefly review completely random measures, a family of pure-jump non-negative stochastic processes that are simple to construct and amenable for posterior computation. We then present nonparametric Bayesian latent variable models based on the beta process, Bernoulli process, gamma process, Poisson process, and in particular, the negative binomial process. Specifically, for continuous data, we discuss dictionary learning with the beta-Bernoulli process and dependent hierarchical beta process, and for count data, we present the beta-negative binomial process and Poisson factor analysis. Furthermore, we discuss how the seeming disjoint count and mixture modelings can be united under the negative binomial processes framework, providing new opportunities to build mixture and hierarchical mixture models with better data fitting, more efficient inference and more flexible model constructions. We show successful applications of our nonparametric Bayesian latent variable models to image processing, topic modeling and count data analysis.
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  •  TALK   A Pole-Placement Approach to the Design of Robust Linear Multivariable Control Systems
    Date: Thursday, July 19, 2012
    Speaker: Rick Vaccaro, University of Rhode Island
    MERL Host: Scott Bortoff
    Brief
    • The ability to directly specify the closed-loop poles of a multivariable control system is a major benefit of pole-placement algorithms for calculating state-feedback and observer gains. The drawback of these algorithms is the lack of any guarantee on the stability robustness of the resulting control system. The optimal control approach for calculating state-feedback gains (LQR) has a certain guaranteed robustness, but adding an observer (i.e. Kalman filter, LQG) can result in arbitrarily poor robustness. In this talk, a new pole-placement approach is introduced for calculating state-feedback and observer gains. The new approach optimizes robustness and gives impressive results, particularly for output feedback, observer-based control systems.
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  •  TALK   Threat Assessment and Semi-Autonomous Control of Manned and Unmanned Vehicles
    Date & Time: Monday, July 16, 2012; 2:00 PM
    Speaker: Dr. Karl Iagnemma, Director, MIT Robotic Mobility Group
    MERL Host: Stefano Di Cairano
    Brief
    • Operator error is a significant factor in a majority of manned and unmanned vehicle accidents. In this talk, a framework for semi-autonomous vehicle accident avoidance will be presented that has been shown to effectively mitigate collisions caused by operator error. The framework analyzes sensor data (from vision and/or LIDAR data) to identify "no go" regions in the environment, and automatically synthesize constraints on vehicle position. An optimal trajectory and associated control inputs are then found via linear or nonlinear model predictive control. The "threat" to the vehicle is quantified from various metrics computed over the optimal trajectory. A number of approaches for arbitrating between operator and control system authority, based on the predicted threat, will be discussed. Extensive simulation and experimental testing will be described for both manned and unmanned scenarios. Future directions in threat assessment and semi-autonomous control, based on the integration of vision-based sensing and active steering control, will also be discussed.
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  •  TALK   Applications of Mobile Augmented Reality and Pervasive Computing in Architecture, Engineering, and Construction
    Date & Time: Tuesday, July 10, 2012; 11:00 AM
    Speaker: Prof Vineet Kamat, University of Michigan
    Research Area: Computer Vision
    Brief
    • This talk will present ongoing research at the University of Michigan Laboratory for Interactive Visualization in Engineering (LIVE) that is exploring applications of mobile pervasive computing and visualization in design, engineering, and construction. Findings from three specific research projects will be presented: Interactive Visualization of Construction Operations in Mobile Outdoor Augmented Reality; Rapid Building Damage Evaluation using Augmented Reality and Structural Simulation; and Location-Aware Contextual Information Access and Retrieval for Rapid On-Site Decision Making. In each case, the development of fundamental algorithms, their implementation as reusable and modular software, and their implementation in the engineering applications will be described.
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  •  TALK   Quadratic Gaussian Multiterminal Source Coding
    Date & Time: Friday, July 6, 2012; 12:00 PM
    Speaker: Zixiang Xiong, Texas A&M University
    MERL Host: Anthony Vetro
    Brief
    • Driven by a host of emerging applications, distributed source coding has assumed renewed interest in the past decade. Although the Slepian-Wolf theorem has been known for almost 40 years and progresses have been made recently on the rate region of quadratic Gaussian two-terminal source coding, finding the sum-rate bound of quadratic Gaussian multiterminal source coding with more than two terminals is still an open problem. In this talk, I'll briefly go over existing results on distributed source coding problems before describing a set of new results we obtained recently.
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  •  TALK   Sparse projections onto convex sets
    Date: Tuesday, July 3, 2012
    Speaker: Prof. Volkan Cevher, EPFL
    MERL Host: Petros Boufounos
    Brief
    • Many natural and man-made signals exhibit a few degrees of freedom relative to their dimension due to natural parameterizations or constraints. The inherent low-dimensional structure of such signals are mathematically modeled via combinatorial and geometric concepts, such as sparsity, unions-of-subspaces, or spectral sets, and are now revolutionizing the way we address linear inverse problems from incomplete data.

      In this talk, we describe a set of structured sparse models for constrained linear inverse problems that feature exact and epsilon-approximate projections in polynomial time. We pay particular attention to the sparsity models based on matroids, multi-knapsack, and clustering as well as spectrally constrained models. We then study sparse projections onto convex sets, such as the (general) simplex, and ell-1,2,inf balls. Finally, we describe a hybrid optimization framework which explicitly leverages these non-convex models along with additional convex constraints to obtain better recovery performance in compressive sensing, learn interpretable sparse densities from finite samples, and improved sparse Markowitzs portfolios with better return/cost performance.
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  •  TALK   Visual 3D/4D modeling of urban places and events
    Date & Time: Friday, June 29, 2012; 2:30 PM
    Speaker: Prof. Marc Pollefeys, ETH Zurich and UNC Chapel Hill
    Research Area: Computer Vision
    Brief
    • One of the fundamental problems of computer vision is to extract 3D shape and motion from images. This can be achieved when a scene or object is observed from different viewpoints or over a period of time. First, we will discuss image-based 3D modeling and localization in large environments, e.g. urban 3D reconstruction from vehicle-borne cameras and (geo)localization from mobile-phone images. In this context, we will discuss some of the challenges an opportunities offered by symmetries of architectural structures. We will also discuss how changes in an urban environment can be detected from images, leading to the possibility to efficiently acquire 4D models. In addition to explicit 4D modeling of an event, we'll consider the possibility to perform interactive video-based rendering from casually captured videos.
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  •  EVENT   ACC 2012 - Sponsored Session: Oppportunities at Mitsubishi Electric Research
    Date & Time: Wednesday, June 27, 2012; 12:00 PM - 1:30 PM
    MERL Contact: Scott Bortoff
    Location: Montreal, Canada
    Brief
    • In this session, MERL researcher Scott Bortoff will describe Mitsubishi Electric Corporation (MELCO)'s businesses, discuss mechatronics and controls research at MERL and describe opportunities for collaboration and employment. Areas of current research interest include optimal control especially of nonlinear and hybrid systems, model predictive control, nonlinear dynamical systems, and modeling and control of multi-physical heterogeneous systems. Research projects at MERL typically address fundamental problems that are industrially-motivated, and involve application of advanced control theory or dynamical systems theory to MELCO products resulting in new technology that is transferred into the corporate R&D laboratories for subsequent product development. Areas of current application include elevators, HVAC, power generation and distribution, satellites, robot manipulation, servo systems and laser processing systems. MERL has a tradition of open collaboration and hosts visitors and interns especially during the summer months when our population increases by 50%. Researchers and students who have an interest in collaboration, visits, sabbatical leaves or permanent employment are invited.
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  •  EVENT   ACC 2012 - The 2012 American Control Conference
    Date: Wednesday, June 27, 2012 - Friday, June 29, 2012
    Location: Montreal, Canada
    Brief
    • MERL is a sponsor for ACC 2012, the 2012 American Control Conference.
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  •  TALK   Toward Efficient and Robust Human Pose Estimation
    Date & Time: Tuesday, June 26, 2012; 12:00 PM
    Speaker: Min Sun, University of Michigan
    Research Area: Computer Vision
    Brief
    • Robust human pose estimation is a challenging problem in computer vision in that body part configurations are often subject to severe deformations and occlusions. Moreover, efficient pose estimation is often a desirable requirement in many applications. The trade-off between accuracy and efficiency has been explored in a large number of approaches. On the one hand, models with simple representations (like tree or star models) can be efficiently applied in pose estimation problems. However, these models are often prone to body part misclassification errors. On the other hand, models with rich representations (i.e., loopy graphical models) are theoretically more robust, but their inference complexity may increase dramatically. In this talk, we present an efficient and exact inference algorithm based on branch-and-bound to solve the human pose estimation problem on loopy graphical models. We show that our method is empirically much faster (about 74 times) than the state-of-the-art exact inference algorithm [Sontag et al. UAI'08]. By extending a state-of-the-art tree model [Sapp et al. ECCV'10] to a loopy graphical model, we show that the estimation accuracy improves for most of the body parts (especially lower arms) on popular datasets such as Buffy [Ferrari et al. CVPR'08] and Stickmen [Eichner and Ferrari BMVC'09] datasets. Our method can also be used to exactly solve most of the inference problems of Stretchable Models [Sapp et al. CVPR'11] on video sequences (which contains a few hundreds of variables) in just a few minutes. Finally, we show that the novel inference algorithm can potentially be used to solve human behavior understanding and biological computation problems.
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  •  TALK   A Real-Time Algorithm for Nonlinear Model Predictive Control and Its Applications
    Date & Time: Monday, June 25, 2012; 10:30 AM
    Speaker: Prof. Toshiyuki Ohtsuka, Osaka University
    MERL Host: Stefano Di Cairano
    Brief
    • In this talk, a real-time algorithm for nonlinear model predictive control and its applications will be introduced. The continuation method is combined with an efficient linear solver GMRES to trace the time-dependent optimal solution without iterative searches. Applications of the algorithm include position control of an underactuated hovercraft, route tracking of a ship with redundant actuators, and path generation for an automobile. Automatic code generation by symbolic computation and other related topics will also be introduced.
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  •  TALK   Cooperative Cuts: Coupling Edges via Submodularity
    Date & Time: Thursday, April 12, 2012; 12:00 PM
    Speaker: Dr. Stefanie Jegelka, UC Berkeley
    Research Area: Computer Vision
    Brief
    • Graph cuts that represent pairwise Markov random fields have been a popular tool in computer vision, but they have some well-known shortcomings that arise from their locality and conditional independence assumptions. We therefore extend graph cuts to "cooperative cuts", where "cooperating" graph edges incur a lower combined cost. This cooperation is modeled by submodular functions on edges. The resulting family of global energy functions includes recent models in computer vision and also new critieria which e.g. significantly improve image segmentation results for finely structured objects and for images with variation in contrast. While "minimum cooperative cut" is NP-hard, the underlying indirect submodularity and the graph structure enable efficient approximations.

      In the second part of the talk, I will switch topics and briefly address Hilbert space embeddings of distributions. With the kernel trick, such embeddings help generalize clustering objectives to consider higher-order moments of distributions instead of merely point locations.
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  •  EVENT   ICASSP 2012 - Special Session on Signal-Processing Challenges and Opportunities in Depth Cameras
    Date & Time: Friday, March 30, 2012; 2:00 PM - 4:00 PM
    MERL Contact: Anthony Vetro
    Location: Kyoto, Japan
    Brief
    • Anthony Vetro co-organized a Special Session of ICASSP 2012 on Signal-Processing Challenges and Opportunities in Depth Cameras. ICASSP 2012 will be held in Kyoto, Japan, in March 2012.
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  •  TALK   Control Design with Uncertain Predictions in Autonomous Systems: Theory and Practice.
    Date & Time: Friday, March 16, 2012; 10:00 AM
    Speaker: Prof. Francesco Borrelli, UC Berkeley
    MERL Host: Stefano Di Cairano
    Brief
    • Forecasts will play an increasingly important role in the next generation of autonomous and semi-autonomous systems. In nominal conditions, predictions of system dynamics, human behavior and environmental envelope can be used by the control algorithm to improve safety and performance of the resulting system. However, in practice, constraint satisfaction, performance guarantees and real-time computation are challenged by the (1) growing complexity of the engineered system, (2) uncertainty in the human/machine interaction and (3) uncertainty in the environment where the system operates.

      In this talk I will present the theory and tools that we have developed over the past ten years for the systematic design of predictive controllers for uncertain linear and nonlinear systems. I will first provide an overview of our theoretical efforts. Then, I will focus on our recent results in addressing constraint satisfaction and real-time computation in nonlinear systems and large-scale networked systems. Throughout the talk I will use two applications to motivate our research and show the benefits of the proposed techniques: Safe Autonomous Cars and Green Intelligent Buildings.
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  •  TALK   Research and Development in JSK Robotics Lab, Univ. of Tokyo
    Date & Time: Thursday, March 8, 2012; 9:30 AM
    Speaker: Prof. Masayuki Inaba, Professor, Director of JSK Robotics Lab<br /> Department of Creative Informatics<br /> Department of Mechano-Informatics<br /> Graduate School of Information Technology and Science<br /> The University of Tokyo
    Brief
    • This talk introduces a history and ongoing activities of the research and development in JSK Robotics Lab, The University of Tokyo including hand-eye coordination in rope handling, correlation-based tracking vision, vision-based robotics, wireless remote-brained approach, whole-body behaviors on humanoids, tactile deformable devices for robot sensor suit, musculoskeletal spined humanoids, power systems for human speed and torque perfomance, learning and assistive activities on HRP2 (Japanese Humanoid Robot Project Platform) and PR2 (Willow Garages's Personal Robot Platform for Open Source Robot Operating System:ROS), common software architecture in all JSK robots, and their mother environment for inherited research and development in JSK.
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  •  TALK   Learning Intermediate-Level Representations of Form and Motion from Natural Movies
    Date & Time: Wednesday, February 22, 2012; 11:00 AM
    Speaker: Dr. Charles Cadieu, McGovern Institute for Brain Research, MIT
    MERL Host: Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • The human visual system processes complex patterns of light into a rich visual representation where the objects and motions of our world are made explicit. This remarkable feat is performed through a hierarchically arranged series of cortical areas. Little is known about the details of the representations in the intermediate visual areas. Therefore, we ask the question: can we predict the detailed structure of the representations we might find in intermediate visual areas?

      In pursuit of this question, I will present a model of intermediate-level visual representation that is based on learning invariances from movies of the natural environment and produces predictions about intermediate visual areas. The model is composed of two stages of processing: an early feature representation layer, and a second layer in which invariances are explicitly represented. Invariances are learned as the result of factoring apart the temporally stable and dynamic components embedded in the early feature representation. The structure contained in these components is made explicit in the activities of second-layer units that capture invariances in both form and motion. When trained on natural movies, the first-layer produces a factorization, or separation, of image content into a temporally persistent part representing local edge structure and a dynamic part representing local motion structure. The second-layer units are split into two populations according to the factorization in the first-layer. The form-selective units receive their input from the temporally persistent part (local edge structure) and after training result in a diverse set of higher-order shape features consisting of extended contours, multi-scale edges, textures, and texture boundaries. The motion-selective units receive their input from the dynamic part (local motion structure) and after training result in a representation of image translation over different spatial scales and directions, in addition to more complex deformations. These representations provide a rich description of dynamic natural images, provide testable hypotheses regarding intermediate-level representation in visual cortex, and may be useful representations for artificial visual systems.
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  •  TALK   User-guided 2D-to-3D Conversion
    Date & Time: Tuesday, February 21, 2012; 12:00 PM
    Speaker: Dimitri Androutsos, Richard Rzeszutek, Ryerson University
    MERL Host: Anthony Vetro
    Brief
    • The problem of converting monoscopic footage into stereoscopic or multi-view content is inherently difficult and ill-posed. On the surface, this does not appear to be the case as the problem may be summed up as, "Given single-view image or video, create one or more views as if they were taken from a different camera view." However, capturing a three-dimensional scene as a two-dimensional image is a lossy process and any information regarding the distance of objects to the camera is lost. Methods exist for extracting depth information from a monoscopic view and it is possible to obtain metrically-correct depth estimates under certain conditions. But since conversion is primarily used as a post-processing stage in film production, the user requires a degree of control over the results. This, in turn, makes it ill-posed as there is no way to know ahead of time what the user wants from the conversion. In this talk we will present the work being done at Ryerson University on user-guided 2D-to-3D conversion. In particular, we will focus on how existing image segmentation techniques may be combined to produce reasonable depth maps for conversion while still providing complete control to the user. We will also discuss how our research can be applied to both images and video without any significant alterations to our methods.
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  •  EVENT   99th MPEG meeting
    Date: Monday, February 6, 2012 - Friday, February 10, 2012
    MERL Contact: Anthony Vetro
    Location: San Jose, CA
    Brief
    • MERL is a sponsor for the 99th MPEG meeting to be held in San Jose, CA, in February 2012. MERL researcher Anthony Vetro serves as Head of the US Delegation to MPEG.
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  •  TALK   Secure Computation and Interference in Networks: Performance Limits and Efficient Protocols
    Date & Time: Wednesday, January 4, 2012; 12:00 PM
    Speaker: Dr. Ye Wang, AgaMatrix, Inc.
    Brief
    • In the field of Secure Multi-party Computation, the general objective is to design protocols that allow a group of parties to securely compute functions of their collective private data, while maintaining privacy (in that no parties reveal any more information about their personal data than necessary) and ensuring correctness (in that no parties can disrupt or influence the computation beyond the affect of changing their input data). Information theoretic approaches toward this broad problem, that provide provable (unconditional) security guarantees (even against adversaries that have unbounded computational power), have established that general computation is possible in a variety of scenarios. However, these general solutions are not always the most efficient or finely tuned to the requirements of specific problems and applications.

      In this talk, we will overview our work toward the development of efficient information theoretic approaches for secure multi-party computation applications within the common theme of secure computation and inference over a distributed data network. These applications include:

      1) private information retrieval, where the objective is to privately obtain data without revealing what was selected;
      2) secure statistical analysis, the problem of extracting statistics without revealing anything else about the underlying distributed data;
      3) secure sampling, which is the secure distributed generation of new data with a given joint distribution; and
      4) secure authentication, where the identity of a party needs to authenticated via inference on his credentials and stored registration data.

      Our contributions toward these applications include the following. We proposed a novel oblivious transfer protocol, applicable to private information retrieval, that trades off a small amount privacy for a drastic increase in efficiency. We leveraged a dimensionality reduction that exploits functional structure to simultaneously achieve arbitrarily high accuracy and efficiency in protocols that perform secure statistical analysis of distributed databases. Toward characterizing the region of distributions that can be securely sampled from scratch, we fully characterized the two-party scenario and provided inner and outer bounds on the multi-party scenario. Toward enabling secure distributed authentication, we proposed a two-factor secure biometric authentication system that is robust against the compromise of registered biometric data, allowing for revocability and providing resistance against cross-enrollment attacks.
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  •  TALK   Electrical Power Storage Technology
    Date & Time: Tuesday, December 20, 2011; 12:00 PM
    Speaker: Olivia Leitermann, MIT
    MERL Host: Daniel Nikovski
    Research Area: Data Analytics
    Brief
    • Ancillary services such as frequency regulation are required for reliable operation of the electric grid. Currently, the same traditional thermal generators that supply bulk power also perform nearly all frequency regulation. Instead, using high power energy storage resources to provide frequency regulation can allow traditional thermal generators to operate more smoothly. However, using energy storage alone for frequency regulation would require an unreasonably large energy storage capacity. Duration curves for energy capacity and instantaneous ramp rate are used to evaluate the requirements and benefits of using energy storage for a component of frequency regulation. High-pass filtering and closed-loop control are used to separate the portion of a frequency regulation control signal suitable for provision by an energy storage unit from the portion suitable for provision by traditional thermal generating resources. Not all frequency regulation signals are equally amenable to the filtering approach used here. Data from two U.S. control areas are used to demonstrate the techniques and the results are compared.
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