News & Events

211 News items and Awards were found.




  •  NEWS   Computer vision and robotics researcher Siddarth Jain appointed as an Associate Editor for the IEEE Robotics and Automation Letters (RA-L)
    Date: October 13, 2020
    MERL Contact: Siddarth Jain
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Robotics
    Brief
    • Computer vision and robotics researcher, Siddarth Jain, has been appointed to the editorial board of the IEEE Robotics and Automation Letters (RA-L) as an Associate Editor. Siddarth joined MERL in September 2019 after obtaining his Ph.D. in robotics from Northwestern University, where he developed novel robotics systems to help people with motor-impairments in performing activities of daily living tasks.

      RA-L publishes peer-reviewed articles in areas of robotics and automation. RA-L also provides a unique feature to the authors with the opportunity to publish a paper in a peer-reviewed journal and present the same paper at the annual flagship robotics conferences of IEEE RAS, including ICRA, IROS, and CASE.
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  •  NEWS   Anoop Cherian gave an invited talk at the Multi-modal Video Analysis Workshop, ECCV 2020
    Date: August 23, 2020
    Where: European Conference on Computer Vision (ECCV), online, 2020
    MERL Contact: Anoop Cherian
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Speech & Audio
    Brief
    • MERL Principal Research Scientist Anoop Cherian gave an invited talk titled "Sound2Sight: Audio-Conditioned Visual Imagination" at the Multi-modal Video Analysis workshop held in conjunction with the European Conference on Computer Vision (ECCV), 2020. The talk was based on a recent ECCV paper that describes a new multimodal reasoning task called Sound2Sight and a generative adversarial machine learning algorithm for producing plausible video sequences conditioned on sound and visual context.
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  •  NEWS   MERL's Scene-Aware Interaction Technology Featured in Mitsubishi Electric Corporation Press Release
    Date: July 22, 2020
    Where: Tokyo, Japan
    MERL Contacts: Siheng Chen; Anoop Cherian; Bret Harsham; Chiori Hori; Takaaki Hori; Jonathan Le Roux; Tim Marks; Alan Sullivan; Anthony Vetro
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Speech & Audio
    Brief
    • Mitsubishi Electric Corporation announced that the company has developed what it believes to be the world’s first technology capable of highly natural and intuitive interaction with humans based on a scene-aware capability to translate multimodal sensing information into natural language.

      The novel technology, Scene-Aware Interaction, incorporates Mitsubishi Electric’s proprietary Maisart® compact AI technology to analyze multimodal sensing information for highly natural and intuitive interaction with humans through context-dependent generation of natural language. The technology recognizes contextual objects and events based on multimodal sensing information, such as images and video captured with cameras, audio information recorded with microphones, and localization information measured with LiDAR.

      Scene-Aware Interaction for car navigation, one target application, will provide drivers with intuitive route guidance. The technology is also expected to have applicability to human-machine interfaces for in-vehicle infotainment, interaction with service robots in building and factory automation systems, systems that monitor the health and well-being of people, surveillance systems that interpret complex scenes for humans and encourage social distancing, support for touchless operation of equipment in public areas, and much more. The technology is based on recent research by MERL's Speech & Audio and Computer Vision groups.


      Demonstration Video:



      Link:

      Mitsubishi Electric Corporation Press Release
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  •  NEWS   MERL researchers presenting three papers at ICML 2020
    Date: July 12, 2020 - July 18, 2020
    Where: Vienna, Austria (virtual this year)
    MERL Contacts: Mouhacine Benosman; Anoop Cherian; Devesh Jha; Daniel Nikovski
    Research Areas: Artificial Intelligence, Computer Vision, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Robotics
    Brief
    • MERL researchers are presenting three papers at the International Conference on Machine Learning (ICML 2020), which is virtually held this year from 12-18th July. ICML is one of the top-tier conferences in machine learning with an acceptance rate of 22%. The MERL papers are:

      1) "Finite-time convergence in Continuous-Time Optimization" by Orlando Romero and Mouhacine Benosman.

      2) "Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?" by Kei Ota, Tomoaki Oiki, Devesh Jha, Toshisada Mariyama, and Daniel Nikovski.

      3) "Representation Learning Using Adversarially-Contrastive Optimal Transport" by Anoop Cherian and Shuchin Aeron.
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  •  NEWS   MERL researchers presenting four papers and organizing two workshops at CVPR 2020 conference
    Date: June 14, 2020 - June 19, 2020
    MERL Contacts: Siheng Chen; Anoop Cherian; Michael Jones; Toshiaki Koike-Akino; Tim Marks; Kuan-Chuan Peng; Ye Wang
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • MERL researchers are presenting four papers (two oral papers and two posters) and organizing two workshops at the IEEE/CVF Computer Vision and Pattern Recognition (CVPR 2020) conference.

      CVPR 2020 Orals with MERL authors:
      1. "Dynamic Multiscale Graph Neural Networks for 3D Skeleton Based Human Motion Prediction," by Maosen Li, Siheng Chen, Yangheng Zhao, Ya Zhang, Yanfeng Wang, Qi Tian
      2. "Collaborative Motion Prediction via Neural Motion Message Passing," by Yue Hu, Siheng Chen, Ya Zhang, Xiao Gu

      CVPR 2020 Posters with MERL authors:
      3. "LUVLi Face Alignment: Estimating Landmarks’ Location, Uncertainty, and Visibility Likelihood," by Abhinav Kumar, Tim K. Marks, Wenxuan Mou, Ye Wang, Michael Jones, Anoop Cherian, Toshiaki Koike-Akino, Xiaoming Liu, Chen Feng
      4. "MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird’s Eye View Maps," by Pengxiang Wu, Siheng Chen, Dimitris N. Metaxas

      CVPR 2020 Workshops co-organized by MERL researchers:
      1. Fair, Data-Efficient and Trusted Computer Vision
      2. Deep Declarative Networks.
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  •  NEWS   MERL presenting 13 papers and an industry talk at ICASSP 2020
    Date: May 4, 2020 - May 8, 2020
    Where: Virtual Barcelona
    MERL Contacts: Karl Berntorp; Petros Boufounos; Chiori Hori; Takaaki Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Yanting Ma; Hassan Mansour; Niko Moritz; Philip Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern; Siheng Chen
    Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & Audio
    Brief
    • MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.

      Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, array processing, and parameter estimation. Videos for all talks are available on MERL's YouTube channel, with corresponding links in the references below.

      This year again, MERL is a sponsor of the conference and will be participating in the Student Job Fair; please join us to learn about our internship program and career opportunities.

      ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year. Originally planned to be held in Barcelona, Spain, ICASSP has moved to a fully virtual setting due to the COVID-19 crisis, with free registration for participants not covering a paper.
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  •  NEWS   MERL Scientists Presenting 11 Papers at IEEE Global Communications Conference (GLOBECOM) 2019
    Date: December 9, 2019 - December 13, 2019
    Where: Waikoloa, Hawaii, USA
    MERL Contacts: Jianlin Guo; Kyeong Jin (K.J.) Kim; Toshiaki Koike-Akino; Rui Ma; Philip Orlik; Pu (Perry) Wang
    Research Areas: Communications, Computer Vision, Machine Learning, Signal Processing, Information Security
    Brief
    • MERL Signal Processing scientists and collaborators will be presenting 11 papers at the IEEE Global Communications Conference (GLOBECOM) 2019, which is being held in Waikoloa, Hawaii from December 9-13, 2019. Topics to be presented include recent advances in power amplifier, MIMO algorithms, WiFi sensing, video casting, visible light communications, user authentication, vehicular communications, secrecy, and relay systems, including sophisticated machine learning applications. A number of these papers are a result of successful collaboration between MERL and world-leading Universities including: Osaka University, University of New South Wales, Oxford University, Princeton University, South China University of Technology, Massachusetts Institute of Technology and Aalborg University.

      GLOBECOM is one of the IEEE Communications Society’s two flagship conferences dedicated to driving innovation in nearly every aspect of communications. Each year, more than 3000 scientific researchers and their management submit proposals for program sessions to be held at the annual conference. Themed “Revolutionizing Communications,” GLOBECOM2019 will feature a comprehensive high-quality technical program including 13 symposia and a variety of tutorials and workshops to share visions and ideas, obtain updates on latest technologies and expand professional and social networking.
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  •  AWARD   MERL Researchers win Best Paper Award at ICCV 2019 Workshop on Statistical Deep Learning in Computer Vision
    Date: October 27, 2019
    Awarded to: Abhinav Kumar, Tim K. Marks, Wenxuan Mou, Chen Feng, Xiaoming Liu
    MERL Contact: Tim Marks
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • MERL researcher Tim Marks, former MERL interns Abhinav Kumar and Wenxuan Mou, and MERL consultants Professor Chen Feng (NYU) and Professor Xiaoming Liu (MSU) received the Best Oral Paper Award at the IEEE/CVF International Conference on Computer Vision (ICCV) 2019 Workshop on Statistical Deep Learning in Computer Vision (SDL-CV) held in Seoul, Korea. Their paper, entitled "UGLLI Face Alignment: Estimating Uncertainty with Gaussian Log-Likelihood Loss," describes a method which, given an image of a face, estimates not only the locations of facial landmarks but also the uncertainty of each landmark location estimate.
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  •  AWARD   MERL researcher wins Best Visualization Note Award at PacificVis2019 Conference
    Date: April 23, 2019
    Awarded to: Teng-yok Lee
    Research Areas: Artificial Intelligence, Computer Vision, Data Analytics, Machine Learning
    Brief
    • MERL researcher Teng-yok Lee has won the Best Visualization Note Award at the PacificVis 2019 conference held in Bangkok Thailand, from April 23-26, 2019. The paper entitled "Space-Time Slicing: Visualizing Object Detector Performance in Driving Video Sequences" presents a visualization method called Space-Time Slicing to assist a human developer in the development of object detectors for driving applications without requiring labeled data. Space-Time Slicing reveals patterns in the detection data that can suggest the presence of false positives and false negatives.
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  •  NEWS   MERL presenting 16 papers at ICASSP 2019
    Date: May 12, 2019 - May 17, 2019
    Where: Brighton, UK
    MERL Contacts: Petros Boufounos; Anoop Cherian; Chiori Hori; Takaaki Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Tim Marks; Niko Moritz; Philip Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
    Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & Audio
    Brief
    • MERL researchers will be presenting 16 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held in Brighton, UK from May 12-17, 2019. Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, and parameter estimation. MERL is also a sponsor of the conference and will be participating in the student career luncheon; please join us at the lunch to learn about our internship program and career opportunities.

      ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year.
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  •  AWARD   R&D100 award for Deep Learning-based Water Detector
    Date: November 16, 2018
    Awarded to: Ziming Zhang, Alan Sullivan, Hideaki Maehara, Kenji Taira, Kazuo Sugimoto
    MERL Contact: Alan Sullivan
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • Researchers and developers from MERL, Mitsubishi Electric and Mitsubishi Electric Engineering (MEE) have been recognized with an R&D100 award for the development of a deep learning-based water detector. Automatic detection of water levels in rivers and streams is critical for early warning of flash flooding. Existing systems require a height gauge be placed in the river or stream, something that is costly and sometimes impossible. The new deep learning-based water detector uses only images from a video camera along with 3D measurements of the river valley to determine water levels and warn of potential flooding. The system is robust to lighting and weather conditions working well during the night as well as during fog or rain. Deep learning is a relatively new technique that uses neural networks and AI that are trained from real data to perform human-level recognition tasks. This work is powered by Mitsubishi Electric's Maisart AI technology.
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  •  NEWS   MERL Researchers Demonstrate Robot Learning Technology at CEATEC'18
    Date: October 15, 2018 - October 19, 2018
    Where: CEATEC'18, Makuhari Messe, Tokyo
    MERL Contacts: Devesh Jha; Daniel Nikovski; Diego Romeres; Alan Sullivan; Jeroen van Baar; William Yerazunis
    Research Areas: Artificial Intelligence, Computer Vision, Data Analytics, Robotics
    Brief
    • MERL's work on robot learning algorithms was demonstrated at CEATEC'18, Japan's largest IT and electronics exhibition and conference held annually at Makuhari Messe near Tokyo. A team of researchers from the Data Analytics Group at MERL and the Artificial Intelligence Department of the Information Technology Center (ITC) of MELCO presented an interactive demonstration of a model-based artificial intelligence algorithm that learns how to control equipment autonomously. The algorithm developed at MERL constructs models of mechanical equipment through repeated trial and error, and then learns control policies based on these models. The demonstration used a circular maze, where the objective is to drive a ball to the center of the maze by tipping and tilting the maze, a task that is difficult even for humans; approximately half of the CEATEC'18 visitors who tried to steer the ball by means of a joystick could not bring it to the center of the maze within one minute. In contrast, MERL's algorithm successfully learned how to drive the ball to the goal within ten seconds without the need for human programming. The demo was at the entrance of MELCO's booth at CEATEC'18, inviting visitors to learn more about MELCO's many other AI technologies on display, and was seen by an estimated more than 50,000 visitors over the five days of the expo.
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  •  NEWS   MERL Researchers Demonstrate New Model-Based AI Learning Technology for Equipment Control
    Date: February 14, 2018
    Where: Tokyo, Japan
    MERL Contacts: Devesh Jha; Daniel Nikovski; Diego Romeres; William Yerazunis; Jeroen van Baar; Alan Sullivan
    Research Areas: Optimization, Computer Vision
    Brief
    • New technology for model-based AI learning for equipment control was demonstrated by MERL researchers at a recent press release event in Tokyo. The AI learning method constructs predictive models of the equipment through repeated trial and error, and then learns control rules based on these models. The new technology is expected to significantly reduce the cost and time needed to develop control programs in the future. Please see the link below for the full text of the Mitsubishi Electric press release.
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  •  NEWS   Andrew Knyazev (MERL) invited to 2018 MathWorks Research Summit
    Date: June 2, 2018 - June 4, 2018
    Where: Newton, Massachusetts (USA)
    Research Areas: Control, Computer Vision, Dynamical Systems, Machine Learning, Data Analytics
    Brief
    • Dr. Andrew Knyazev of MERL has accepted an invitation to participate at the 2018 MathWorks Research Summit. The objective of the Research Summit is to provide a forum for leading researchers in academia and industry to explore the latest research and technology results and directions in computation and its use in technology, engineering, and science. The event aims to foster discussion among scientists, engineers, and research faculty about challenges and research opportunities for the respective communities with a particular interest in exploring cross-disciplinary research avenues.
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  •  NEWS   MERL invites applications for Visiting Faculty
    Date: February 15, 2018
    Brief
    • University faculty members are invited to spend part or all of their sabbaticals at MERL, pursuing projects of their own choosing in collaboration with MERL researchers.

      To apply, a candidate should identify and contact one or more MERL researchers with whom they would like to collaborate. The applicant and a MERL researcher will jointly prepare a proposal that the researcher will champion internally. Please visit the visiting faculty web page for further details: http://www.merl.com/employment/visiting-faculty.php.

      The application deadline for positions starting in Summer/Fall 2018 is February 15, 2018.
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  •  NEWS   Tim Marks to give invited Keynote talk at AMFG 2017 Workshop, at ICCV 2017
    Date: October 28, 2017
    Where: Venice, Italy
    MERL Contact: Tim Marks
    Research Area: Machine Learning
    Brief
    • MERL Senior Principal Research Scientist Tim K. Marks will give an invited keynote talk at the 2017 IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG 2017). The workshop will take place On October 28, 2017, at the International Conference on Computer Vision (ICCV 2017) in Venice, Italy.
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  •  NEWS   MERL presents 5 papers at ICIP 2017, Anthony Vetro serves as general co-chair
    Date: September 17, 2017 - September 20, 2017
    Where: Beijing, China
    MERL Contacts: Petros Boufounos; Dehong Liu; Hassan Mansour; Huifang Sun; Anthony Vetro
    Research Areas: Computer Vision, Computational Sensing, Digital Video
    Brief
    • MERL presented 5 papers at the IEEE International Conference on Image Processing (ICIP), which was held in Beijing, China from September 17-20, 2017. ICIP is a flagship conference of the IEEE Signal Processing Society and approximately 1300 people attended the event. Anthony Vetro served as General Co-chair for the conference.
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  •  NEWS   MERL attends The Grace Hopper Celebration of Women in Computing
    Date: October 4, 2017 - October 6, 2017
    Where: Orange County Convention Center, Orlando, FL
    MERL Contacts: Elizabeth Phillips; Jinyun Zhang
    Brief
    • Every year, women technologists and the best minds in computing convene to highlight the contributions of women to computing. The Anita Borg Institute co-presents GHC with the Association of Computing Machinery (ACM).

      The conference results in collaborative proposals, networking and mentoring for our attendees. Conference presenters are leaders in their respective fields, representing industry, academia and government.
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  •  NEWS   MERL Researcher Tim Marks presents an invited talk at MIT Lincoln Laboratory
    Date: April 27, 2017
    Where: Lincoln Laboratory, Massachusetts Institute of Technology
    MERL Contact: Tim Marks
    Research Area: Machine Learning
    Brief
    • MERL researcher Tim K. Marks presented an invited talk as part of the MIT Lincoln Laboratory CORE Seminar Series on Biometrics. The talk was entitled "Robust Real-Time 2D Face Alignment and 3D Head Pose Estimation."

      Abstract: Head pose estimation and facial landmark localization are key technologies, with widespread application areas including biometrics and human-computer interfaces. This talk describes two different robust real-time face-processing methods, each using a different modality of input image. The first part of the talk describes our system for 3D head pose estimation and facial landmark localization using a commodity depth sensor. The method is based on a novel 3D Triangular Surface Patch (TSP) descriptor, which is viewpoint-invariant as well as robust to noise and to variations in the data resolution. This descriptor, combined with fast nearest-neighbor lookup and a joint voting scheme, enable our system to handle arbitrary head pose and significant occlusions. The second part of the talk describes our method for face alignment, which is the localization of a set of facial landmark points in a 2D image or video of a face. Face alignment is particularly challenging when there are large variations in pose (in-plane and out-of-plane rotations) and facial expression. To address this issue, we propose a cascade in which each stage consists of a Mixture of Invariant eXperts (MIX), where each expert learns a regression model that is specialized to a different subset of the joint space of pose and expressions. We also present a method to include deformation constraints within the discriminative alignment framework, which makes the algorithm more robust. Both our 3D head pose and 2D face alignment methods outperform the previous results on standard datasets. If permitted, I plan to end the talk with a live demonstration.
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  •  NEWS   MERL researcher Tim Marks presents invited talk at University of Utah
    Date: April 10, 2017
    Where: University of Utah School of Computing
    MERL Contact: Tim Marks
    Research Area: Machine Learning
    Brief
    • MERL researcher Tim K. Marks presented an invited talk at the University of Utah School of Computing, entitled "Action Detection from Video and Robust Real-Time 2D Face Alignment."

      Abstract: The first part of the talk describes our multi-stream bi-directional recurrent neural network for action detection from video. In addition to a two-stream convolutional neural network (CNN) on full-frame appearance (images) and motion (optical flow), our system trains two additional streams on appearance and motion that have been cropped to a bounding box from a person tracker. To model long-term temporal dynamics within and between actions, the multi-stream CNN is followed by a bi-directional Long Short-Term Memory (LSTM) layer. Our method outperforms the previous state of the art on two action detection datasets: the MPII Cooking 2 Dataset, and a new MERL Shopping Dataset that we have made available to the community. The second part of the talk describes our method for face alignment, which is the localization of a set of facial landmark points in a 2D image or video of a face. Face alignment is particularly challenging when there are large variations in pose (in-plane and out-of-plane rotations) and facial expression. To address this issue, we propose a cascade in which each stage consists of a Mixture of Invariant eXperts (MIX), where each expert learns a regression model that is specialized to a different subset of the joint space of pose and expressions. We also present a method to include deformation constraints within the discriminative alignment framework, which makes the algorithm more robust. Our face alignment system outperforms the previous results on standard datasets. The talk will end with a live demo of our face alignment system.
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  •  NEWS   MERL to present 10 papers at ICASSP 2017
    Date: March 5, 2017 - March 9, 2017
    Where: New Orleans
    MERL Contacts: Petros Boufounos; Takaaki Hori; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Anthony Vetro; Ye Wang
    Research Areas: Computer Vision, Computational Sensing, Digital Video, Information Security, Speech & Audio
    Brief
    • MERL researchers will presented 10 papers at the upcoming IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), to be held in New Orleans from March 5-9, 2017. Topics to be presented include recent advances in speech recognition and audio processing; graph signal processing; computational imaging; and privacy-preserving data analysis.

      ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year.
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  •  NEWS   MERL presents three papers at the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    Date: June 27, 2016 - June 30, 2016
    Where: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV
    MERL Contacts: Michael Jones; Tim Marks
    Research Area: Machine Learning
    Brief
    • MERL researchers in the Computer Vision group presented three papers at the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), which had a paper acceptance rate of 29.9%.
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  •  NEWS   MERL researcher, Oncel Tuzel, gives keynote talk at 2016 International Symposium on Visual Computing
    Date: December 14, 2015 - December 16, 2015
    Where: Las Vegas, NV, USA
    Research Area: Machine Learning
    Brief
    • MERL researcher, Oncel Tuzel, gave a keynote talk at 2016 International Symposium on Visual Computing in Las Vegas, Dec. 16, 2015. The talk was titled: "Machine vision for robotic bin-picking: Sensors and algorithms" and reviewed MERL's research in the application of 2D and 3D sensing and machine learning to the problem of general pose estimation.

      The talk abstract was: For over four years, at MERL, we have worked on the robot "bin-picking" problem: using a 2D or 3D camera to look into a bin of parts and determine the pose, 3D rotation and translation, of a good candidate to pick up. We have solved the problem several different ways with several different sensors. I will briefly describe the sensors and the algorithms. In the first half of the talk, I will describe the Multi-Flash camera, a 2D camera with 8 flashes, and explain how this inexpensive camera design is used to extract robust geometric features, depth edges and specular edges, from the parts in a cluttered bin. I will present two pose estimation algorithms, (1) Fast directional chamfer matching--a sub-linear time line matching algorithm and (2) specular line reconstruction, for fast and robust pose estimation of parts with different surface characteristics. In the second half of the talk, I will present a voting-based pose estimation algorithm applicable to 3D sensors. We represent three-dimensional objects using a set of oriented point pair features: surface points with normals and boundary points with directions. I will describe a max-margin learning framework to identify discriminative features on the surface of the objects. The algorithm selects and ranks features according to their importance for the specified task which leads to improved accuracy and reduced computational cost.
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  •  NEWS   MERL presented 3 papers at the 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
    Date: December 15, 2015
    Where: 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
    MERL Contact: Hassan Mansour
    Research Area: Machine Learning
    Brief
    • MERL researcher Andrew Knyazev gave 3 talks at the 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). The papers were published in IEEE conference proceedings.
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  •  NEWS   Teng-Yok Lee co-chairs Large Data Analysis and Visualization workshop
    Date: October 25, 2015
    Where: Large Data Analysis and Visualization (LDAV)
    Research Area: Computer Vision
    Brief
    • Teng-Yok Lee served as the poster co-chair for the Large Data Analysis and Visualization (LDAV) workshop at IEEEVis 2015 in Chicago, Oct. 25-30. At IEEEVis there were over 2000 attendees and three highly competitive main subconferences (SciVis, InfoVis, and Visual Analytics and Technology (VAST)).
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