News & Events

86 Talks were found.

  •  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 Area: Speech & Audio
  •  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
    • 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.
  •  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
    • 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.
  •  TALK   Modeling and Control of Multi-locomotion Robotic System
    Date & Time: Tuesday, June 14, 2011; 4:00 PM
    Speaker: Tadayoshi Aoyama, Nagoya University
    Research Area: Computer Vision
    • 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.
  •  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
    • 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).
  •  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
    • 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.