News & Events

80 Talks were found.


  •  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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  •  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
    Research Area: Mechatronics
    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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  •  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
    Research Area: Mechatronics
    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
    Research Area: Mechatronics
    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 Areas: Multimedia, 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
    Research Area: Multimedia
    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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  •  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.
    Research Area: Multimedia
    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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  •  TALK   Interesting and unusual forms of autostereo display
    Date & Time: Thursday, December 1, 2011; 11:00 AM
    Speaker: Gregg Favalora, Optics for Hire (OFH)
    MERL Host: Matthew Brand
    Research Area: Algorithms
    Brief
    • I'll give an information-rich survey presentation on "interesting and unusual" forms of autostereo display. It will assume basic knowledge of autostereo, e.g. lenticular and parallax barrier displays [unless, of course, you'd like a few minutes going over the basics.] I will discuss: spatially-multiplexed, time-multiplexed, and multi-projector systems. This includes: non-obvious depth cues, advances in parallax barrier displays, lenticulars, multi-projector / projection onto corrugated screens, scanned illumination, volumetric, and electro-holographic techniques.
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  •  TALK   Scheduling and Medium Access in Wireless Networks
    Date & Time: Friday, November 18, 2011; 12:00 PM
    Speaker: Shreeshankar Bodas, MIT
    Research Area: Multimedia
    Brief
    • We look at the problem of designing "efficient" resource allocation algorithms for wireless networks. The volume of data transferred over the wireless network has been ever-growing, but the resources (time, frequency) are not growing at the same rate. We therefore need to design good resource allocation schemes to guarantee a good quality of service to the users.

      In the first part of the talk, we look at the wireless access network, such as Wi-Fi. We have three objectives: ensure high resource utilization, low user-perceived latency, while keeping the computational burden on the devices to a minimum. An interesting recent result by Shah et al says that these three objectives are incompatible with other, unless P=NP. We design a physical layer-aware medium access algorithm that simultaneously achieves the three objectives, and thereby show that the hardness result by Shah et al is an artifact of a simplistic view of the physical layer.

      The second part of the talk focuses on designing scheduling algorithms for wireless downlink networks, such as a cellular network. Our objectives (again) are high resource utilization, low per-user delay, and a "simple" algorithm. We outline the drawbacks of the classic MaxWeight-type algorithms, and design iterative resource allocation schemes that perform well on all the three fronts.
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  •  TALK   Auxiliary Function Approach to Source Localization and Separation
    Date & Time: Thursday, October 20, 2011; 3:40 PM
    Speaker: Prof. Nobutaka Ono, National Institute of Informatics, Tokyo
    MERL Host: Jonathan Le Roux
    Research Areas: Multimedia, Speech & Audio
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  •  TALK   Analysing Digital Music
    Date & Time: Thursday, October 20, 2011; 2:20 PM
    Speaker: Prof. Mark Plumbley, Queen Mary, London
    MERL Host: Jonathan Le Roux
    Research Areas: Multimedia, Speech & Audio
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  •  TALK   Itakura-Saito nonnegative matrix factorization and friends for music signal decomposition
    Date & Time: Thursday, October 20, 2011; 3:00 PM
    Speaker: Dr. Cedric Fevotte, CNRS - Telecom ParisTech, Paris
    MERL Host: Jonathan Le Roux
    Research Areas: Multimedia, Speech & Audio
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  •  TALK   Image and Sensor-based Navigation in Fluorescence Endoscopy
    Date & Time: Thursday, September 1, 2011; 12:00 PM
    Speaker: Alexander Behrens, RWTH Aachen University
    MERL Host: Anthony Vetro
    Research Area: Multimedia
    Brief
    • Today, photodynamic diagnostics is commonly used for cancer detection in endoscopic interventions of the urinary bladder. Although the visual contrast between benign and malignant tissue is significantly enhanced using fluorescence markers, the field of view (FOV) of the endoscope becomes very limited. This impedes the navigation and the re-identifying of multi-focal tumors for the physician. Thus, new image mosaicking algorithms and visualization methods, which provide larger FOVs in real-time from free-hand bladder scans are developed and will be presented. Furthermore a novel method for an automatic control of seamless inspections using graphs are addressed. Going beyond image processing, a first low-cost inertial 3-D navigation system will be introduced, and a guided navigation tool for tumor re-identification and its application to virtual endoscopy will be discussed.
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  •  TALK   Gigapixel Binary Sensing: Image Acquisition Using Oversampled One-Bit Poisson Statistics
    Date & Time: Wednesday, June 15, 2011; 12:00 PM
    Speaker: Dr. Yue M. Lu, Harvard School of Engineering and Applied Sciences
    MERL Host: Petros Boufounos
    Research Area: Multimedia
    Brief
    • Before the advent of digital image sensors, photography, for the most part of its history, used film to record light information. In this talk, I will present a new digital image sensor that is reminiscent of photographic film. Each pixel in the sensor has a binary response, giving only a one-bit quantized measurement of the local light intensity.

      To analyze its performance, we formulate the binary sensing scheme as a parameter estimation problem based on quantized Poisson statistics. We show that, with a single-photon quantization threshold and large oversampling factors, the Cramer-Rao lower bound of the estimation variance approaches that of an ideal unquantized sensor, that is, as if there were no quantization in the sensor measurements. Furthermore, this theoretical performance bound is shown to be asymptotically achievable by practical image reconstruction algorithms based on maximum likelihood estimators.

      Numerical results on both synthetic data and images taken by a prototype sensor verify the theoretical analysis and the effectiveness of the proposed image reconstruction algorithm. They also demonstrate the benefit of using the new binary sensor in applications involving high dynamic range imaging.

      Joint work with Feng Yang, Luciano Sbaiz and Martin Vetterli.
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  •  TALK   Modeling and Control of Multi-locomotion Robotic System
    Date & Time: Tuesday, June 14, 2011; 4:00 PM
    Speaker: Tadayoshi Aoyama, Nagoya University
    MERL Host: Yuichi Taguchi
    Research Area: Computer Vision
    Brief
    • First, the concept of "Multi-Locomotion Robot" that has multiple types of locomotion is introduced. The robot is developed to achieve a bipedal walk, a quadruped walk and a brachiation, mimicking locomotion ways of a gorilla. It therefore has higher mobility by selecting a proper locomotion type according to its environment and purpose. I show you some experimental videos with respect to realized motions before now.
      Second, I focus on biped walk and talk about detail of bipedal walking. This part proposes a 3-D biped walking algorithm based on Passive Dynamic Autonomous Control (PDAC). The robot dynamics is modeled as an autonomous system of a 3-D inverted pendulum by applying the PDAC concept that is based on the assumption of point contact of the robot foot and the virtual constraint as to robot joints. Due to autonomy, there are two conservative quantities named "PDAC constant", that determine the velocity and direction of the biped walking. We also propose the convergence algorithm to make PDAC constants converge to arbitrary values, so that walking velocity and direction are controllable. Finally, experimental results validate the performance and the energy efficiency of the proposed algorithm.
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  •  TALK   Recursive Sparse Recovery and Applications in Dynamic Imaging
    Date & Time: Friday, June 3, 2011; 11:00 AM
    Speaker: Prof. Namrata Vaswani, Iowa State University
    MERL Host: Petros Boufounos
    Research Area: Multimedia
    Brief
    • In this talk, I will discuss our recent work on Recursive Sparse Recovery (RecSparsRec) and show how it provides novel solutions to two very different problems in dynamic imaging. RecSparsRec refers to recursive approaches to causally recover a time sequence of signals/images from a greatly reduced number of measurements (compared to existing approaches), by utilizing their sparsity.

      The motivating application for RecSparsRec is fast recursive dynamic magnetic resonance imaging (MRI) for real-time applications like MRI-guided surgery. MRI is a technique for cross-sectional imaging that acquires Fourier projections of the cross-section to be reconstructed, one-at-a-time. Thus, the ability to accurately reconstruct using fewer measurements directly translates into reduced scan times. This, along with online (causal) and fast (recursive) reconstruction algorithms, can enable real-time imaging of fast changing physiological phenomena, and thus make real-time MRI feasible. Cross-sectional images of the brain, heart, or other organs are known to be wavelet sparse. Our recent work was the first to observe that, in a time sequence, their sparsity pattern changes quite slowly. Using this fact, we were able to reformulate the RecSparsRec problem as one of sparse reconstruction with partially known support. We introduced a simple, but very powerful, approach called!
      Modified-CS that achieves provably exact reconstruction (in the noise-free case) and whose error is provably stable over time (in the noisy case), with using much fewer measurements than existing work. Our preliminary experiments indicate that Modified-CS needs roughly 5-times fewer measurements than existing MR scanner technology and 1.5-times fewer than existing research literature.

      I will briefly also discuss our ongoing work on the difficult video analysis problem of separating foreground moving objects from a background scene that is itself is changing and dong this in real-time. This can be posed as a recursive robust principal components analysis (PCA) problem in the presence of correlated sparse outliers or equivalently, as a problem of recursive sparse recovery in the presence of very large, but ``low rank" noise (noise with a low rank covariance matrix).
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  •  TALK   Resource Block Embedding: Towards High Throughput Broadband Multimedia Wireless Networks
    Date & Time: Thursday, June 2, 2011; 12:00 PM
    Speaker: Ramesh Annavajjala, MERL
    MERL Host: Philip Orlik
    Research Area: Electronics & Communications
    Brief
    • For orthogonal frequency-division multiplexing (OFDM) based wireless systems, a resource block (RB) in a two-dimensional time-frequency plane is defined as a data block spanned by a number of consecutive OFDM symbols over a number of consecutive subcarriers. Traditionally, RBs contain modulation symbols for data transmission and pilot symbols for channel estimation.

      In this talk, I present a novel approach to RB designs for OFDM systems with multiple antennas at the transmitter and the receiver (i.e., MIMO-OFDM). The proposed approach, termed resource block embedding, does not require explicit pilot symbols to estimate the channel at the receiver, and hence reduces the channel estimation overhead significantly. I describe, in detail, the encoding and decoding algorithms for our proposed embedded resource blocks (ERB) for single-user single-antenna transmission, two transmitter antenna Alamouti code, four transmitter antenna stacked Alamouti code, and multi-stream spatial multiplexing. I also outline construction of ERBs for multi-user MIMO systems.

      This is a joint work with Phil Orlik and Jin Zhang.
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