- Date: February 20, 2015
Research Area: Computer Vision
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- Date: July 11, 2014
Where: R&D Magazine
Research Area: Computer Vision
Brief - A team with members from MERL, ATC, and Meiden received an R&D 100 award for its work on Mitsubishi Electric's MELFA-3D Vision system for industrial robot arms. This system completely automates bin picking a task for picking up parts that are randomly placed in a bin and aligning their poses for assembly processes.
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- Date: February 13, 2014
MERL Contact: Matthew Brand Brief - Mitsubishi Electric Corporation announced its development of advanced optimization algorithms and high-speed calculation methods aimed at optimizing the performance of three practical systems: laser-processing machines for high-speed cutting of sheet metal using the shortest possible trajectories, moon probes achieved with minimized fuel consumption, and particle beam therapies for prompt medical treatments.
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- Date & Time: Friday, October 4, 2013; 12:00 PM
Speaker: Dr. Goksel Dedeoglu, Texas Instruments
Research Area: Computer Vision
Abstract 
There are growing needs to accelerate computer vision algorithms on embedded processors for wide-ranging equipment including mobile phones, network cameras, robots, and automotive safety systems. In our Vision R&D group, we conduct various projects to understand how the vision requirements can be best addressed on Digital Signal Processors (DSP), where the compute bottlenecks are, and how we should evolve our hardware & software architectures to meet our customers' future needs. Towards this end, we build prototypes wherein we design and optimize embedded software for real-world application performance and robustness. In this talk, I will provide examples of vision problems that we have recently tackled.
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- Date: June 29, 2013
Where: International Conference on 3DTV-Conference
Research Area: Computer Vision
Brief - The paper "Model-Based Vehicle Pose Estimation and Tracking in Videos Using Random Forests" by Hodlmoser, M., Micusik, B., Pollegeys, M., Liu, M-Y. and Kampel, M. was presented at the International Conference on 3DTV-Conference.
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- Date & Time: Friday, June 28, 2013; 9:00 AM - 5:00 PM
Location: Portland, Oregon
Research Area: Computer Vision
Brief - Amit Agrawal is the co-organizer of the CCD/PROCAMS 2013 Workshop of Computational Cameras and Displays.
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- Date: June 23, 2013
Where: IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Research Area: Computer Vision
Brief - The papers "Single Image Calibration of Multi-Axial Imaging Systems" by Agrawal, A. and Ramalingam, S., "Joint Geodesic Upsampling of Depth Images" by Liu, M-Y, Tuzel, O. and Taguchi, Y. and "Manhattan Junction Catalogue for Spatial Reasoning of Indoor Scenes" by Ramalingam, S., Pillai, J.K., Jain, A. and Taguchi, Y. were presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
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- Date: June 13, 2013
Where: CIRP Conference on Modeling of Machining Operations (CIRP CMMO)
Research Area: Computer Vision
Brief - The paper "Cutter Workpiece Engagement Calculations for Five-axis Milling using Composite Adaptively Sampled Distance Fields" by Erdim, H. and Sullivan, A. was presented at the CIRP Conference on Modeling of Machining Operations (CIRP CMMO).
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- Date & Time: Thursday, May 23, 2013; 12:00 PM
Speaker: Prof. Raquel Urtasun, TTI-Chicago
Research Area: Computer Vision
Abstract 
The development of autonomous systems that can effectively assist people with everyday tasks is one of the grand challenges in modern computer science. Notable examples are personal robotics for the elderly and people with disabilities, as well as autonomous driving systems which can help decrease fatalities caused by traffic accidents. To achieve full autonomy, multiple perception tasks must be solved: Autonomous systems should sense the environment, recognize the 3D world and interact with it. While most approaches have tackled individual perceptual components in isolation, I believe that the next generation of perceptual systems should reason jointly about multiple tasks.
In this talk I'll argue that there are four key aspects towards developing such holistic models: (i) learning, (ii) inference (iii) representation, and (iv) data. I'll describe efficient Markov random field learning and inference algorithms that exploit both the structure of the problem as well as parallel computation to achieve computational and memory efficiency. I'll demonstrate the effectiveness of our models on a wide variety of examples, and show representations and inference strategies that allow us to achieve state-of-the-art performance and result in several orders of magnitude speed-ups in a variety of challenging tasks, including 3D reconstruction, 3D layout parsing, object detection, semantic segmentation and free text exploitation for holistic visual recognition.
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- Date: May 14, 2013
Where: IEEE International Conference on Robotics & Automation (ICRA)
Research Area: Computer Vision
Brief - The paper "Point-Plane SLAM for Hand-Held 3D Sensors" by Taguchi, Y., Jian, Y-D, Ramalingam, S. and Feng, C. was presented at the IEEE International Conference on Robotics & Automation (ICRA).
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- Date: April 1, 2013
Where: IEEE Transactions on Pattern Analysis and Machine Intelligence
Research Area: Computer Vision
Brief - The article "Support Vector Shape: A Classifier Based Shape Representation" by Nguyen, H. V. and Porikli, F. was published in IEEE Transactions on Pattern Analysis and Machine Intelligence.
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- Date: February 14, 2013
Where: IEEE Transactions on Pattern Analysis and Machine Intelligence
Research Area: Computer Vision
Brief - The article "Nonlinear Camera Response Functions and Image Deblurring: Theoretical Analysis and Practice" by Tai, Y-W, Chen, X., Kim, S., Kim, S.J., Li, F., Yang, J., Yu, J., Matsushita, Y. and Brown, M.S. was published in IEEE Transactions on Pattern Analysis and Machine Intelligence.
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- Date: December 12, 2012
Where: International Conference on Machine Learning and Applications (ICMLA)
Research Area: Machine Learning
Brief - The paper "Compressive Clustering of High-Dimensional Data" by Ruta, A. and Porikli, F. was presented at the International Conference on Machine Learning and Applications (ICMLA).
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- Date & Time: Thursday, November 15, 2012; 12:00 PM
Speaker: Dr. Eduardo Torres-Jara, Worcester Polytechnic Institute
Research Area: Computer Vision
Abstract - This talk presents an alternative approach to robotic manipulation. In this approach, manipulation is mainly guided by tactile feedback as opposed to vision. The motivation behind this approach stems from the fact that manipulating an object necessarily implies coming into contact with it. As a result, directly sensing physical contact seems more important than vision to control the interaction of the object and the robot. In this work, the traditional approach of a highly precise arm guided by a vision system is replaced by one that uses a low mechanical impedance arm with dense tactile sensing and exploration capabilities.
The robots OBRERO and GoBot have been built to implement this approach. We have developed a novel tactile sensing technology and mounted our sensors on the robots' hands. These sensors are biologically inspired and present adequate features for manipulation. The success of this approach is shown by picking up objects in a poorly modeled environment. This task, simple for humans, has been a challenge for robots. The robot can deal with new, unmodeled objects. Specifically, OBRERO can gently contact, explore, lift, and place an object in a different location. It can also detect basic slippage and external forces acting on an object while it is held. These tasks can be performed successfully with very light objects, without fixtures, and on slippery surfaces. Similarly, GoBot is capable of manipulating small objects such as the stones in the game GO. Both OBRERO and GoBot perform all of their manipulations using tactile feedback.
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- Date: November 11, 2012
Where: IEEE International Conference on Pattern Recognition (ICPR)
Research Area: Computer Vision
Brief - The paper "A Grassmann Manifold-based Domain Adaptation Approach" by Zheng, J., Liu, M.-Y., Chellappa, R. and Phillips, P.J. was presented at the IEEE International Conference on Pattern Recognition (ICPR).
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- Date: November 5, 2012
Where: International Symposium on Mixed and Augmented Reality (ISMAR)
Research Area: Computer Vision
Brief - The paper "SLAM Using Both Points and Planes for Hand-Held 3D Sensors" by Taguchi, Y., Jian, Y.-D., Ramalingam, S. and Feng, C. was presented at the International Symposium on Mixed and Augmented Reality (ISMAR).
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- Date: October 29, 2012
Where: CIRP Conference on Process Machine Interactions (PMI)
Research Area: Computer Vision
Brief - The paper "High Accuracy Computation of Geometric Properties of Cutter Workpiece Intersection using Distance Fields for NC Milling" by Erdim, H. and Sullivan, A. was presented at the CIRP Conference on Process Machine Interactions (PMI).
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- Date: October 13, 2012
Where: IEEE International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)
Research Area: Machine Learning
Brief - The paper "Classification and Pose Estimation of Vehicles in Videos by 3D Modeling within Discrete-Continuous Optimization" by Hodlmoser, M., Micusik, B., Liu, M.-Y., Pollefeys, M. and Kaampel, M. was presented at the IEEE International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT).
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- Date: October 7, 2012
Where: European Conference on Computer Vision (ECCV)
Research Area: Computer Vision
Brief - The papers "Motion-Aware Structured Light Using Spatio-Temporal Decodable Patterns" by Taguchi, Y., Agrawal, A. and Tuzel, O., "Rainbow Flash Camera: Depth Edge Extraction Using Complementary Colors" by Taguchi, Y. and "Monocular Visual Odometry and Dense 3D Reconstruction for On-Road Vehicles" by Zhu, M., Ramalingam, S., Taguchi, Y. and Garaas, T. were presented at the European Conference on Computer Vision (ECCV).
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- Date: September 27, 2012
Where: International Journal of Computer Vision
Research Area: Computer Vision
Brief - The article "A Theory of Minimal 3D Point to 3D Plane Registration and Its Generalization" by Ramalingam, S. and Taguchi, Y. was published in International Journal of Computer Vision.
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- Date & Time: Friday, August 17, 2012; 12:00 PM
Speaker: Prof. Hiroshi Kawasaki, Kagoshima University
Research Area: Computer Vision
Abstract - In this talk, I will introduce an overview of my research projects on 3D shape acquisition of moving object. The talk mainly focuses on two parts, the first one is about our 3D shape acquisition technique using projector and camera system and the second is entire shape acquisition using multi-view pro-cam system. I also briefly cover the following topics:
-- Theory of shape from coplanarity technique
-- Texture recovery method on pro-cam system
-- Future plan on medical application of our scanner
Those researches are jointly researched by Prof. Katushi Ikeuchi (Univ. of Tokyo), Prof. Ryo Furukawa (Hiroshima city Univ) and Prof. Ryusuke Sagawa (AIST).
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- Date & Time: Tuesday, July 10, 2012; 11:00 AM
Speaker: Prof Vineet Kamat, University of Michigan
Research Area: Computer Vision
Abstract - 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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- Date & Time: Friday, June 29, 2012; 2:30 PM
Speaker: Prof. Marc Pollefeys, ETH Zurich and UNC Chapel Hill
Research Area: Computer Vision
Abstract - 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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- Date & Time: Tuesday, June 26, 2012; 12:00 PM
Speaker: Min Sun, University of Michigan
Research Area: Computer Vision
Abstract - 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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- Date: June 16, 2012
Where: IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Research Area: Computer Vision
Brief - The papers "Connecting the Dots in Multi-Class Classification: From Nearest Subspace to Collaborative Representation" by Chi, Y. and Porikli, F., "Decomposing Global Light Transport using Time of Flight Imaging" by Wu, D., O'Toole, M., Velten, A., Agrawal, A. and Raskar, R., "Changedetection.net: A New Change Detection Benchmark Dataset" by Goyette, N., Jodoin, P.-M., Porikli, F., Konrad, J. and Ishwar, P. and "A Theory of Multi-Layer Flat Refractive Geometry" by Agrawal, A., Ramalingam, S., Taguchi, Y. and Chari, V. were presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
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