- 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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- 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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- Date: September 18, 2015
Where: IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2015
Research Area: Machine Learning
Brief - MERL researchers A. Knyazev and A. Malyshev gave a talk at the IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2015. The paper was published at the IEEE Xplore conference proceedings.
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- Date: July 13, 2015 - July 17, 2015
Research Area: Machine Learning
Brief - SA group members (M. Liu, S. Lin (intern), S. Ramalingam, O. Tuzel) presented a paper at the Robotics Science and Systems Conference in Rome July 13-17 called 'Layered Interpretation of Street View Images'. The results they reported are now listed as the leader of the benchmark competition sponsored by Daimler. [Note that at that URL ref 2 is from collaboration with Daimler and it uses a FPGA for high speed, whereas MERL result is obtained with desktop computer and GPU.].
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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: 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: January 10, 2012
Where: IEEE Transactions on Pattern Analysis and Machine Intelligence
Research Area: Machine Learning
Brief - The article "Scalable Active Learning for Multi-Class Image Classification" by Joshi, A.J., Porikli, F. and Papanikolopoulos, N. was published in IEEE Transactions on Pattern Analysis and Machine Intelligence.
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- Date: January 1, 2012
Where: Video Analytics for Business Intelligence
Research Area: Machine Learning
Brief - The article "Object Detection & Tracking" by Porikli, F. and Yilmaz, A. was published in the book Video Analytics for Business Intelligence.
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- Date: September 2, 2011
Awarded to: Fatih Porikli and Huseyin Ozkan.
Awarded for: "Data Driven Frequency Mapping for Computationally Scalable Object Detection"
Awarded by: IEEE Advanced Video and Signal Based Surveillance (AVSS)
Research Area: Machine Learning
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- Date: August 30, 2011
Where: IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
Research Area: Machine Learning
Brief - The paper "Data Driven Frequency Mapping for Computationally Scalable Object Detection" by Porikli, F. and Ozkan, H. was presented at the IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).
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- Date: June 25, 2011
Awarded to: Paul A. Viola and Michael J. Jones
Awarded for: "Rapid Object Detection using a Boosted Cascade of Simple Features"
Awarded by: Conference on Computer Vision and Pattern Recognition (CVPR)
MERL Contact: Michael J. Jones
Research Area: Machine Learning
Brief - Paper from 10 years ago with the largest impact on the field: "Rapid Object Detection using a Boosted Cascade of Simple Features", originally published at Conference on Computer Vision and Pattern Recognition (CVPR 2001).
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- Date: March 15, 2011
Where: Machine Vision and Applications
Research Area: Machine Learning
Brief - The article "In-vehicle Camera Traffic Sign Detection and Recognition" by Ruta, A., Porikli, F.M., Watanabe, S. and Li, Y. was published in Machine Vision and Applications.
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- Date: August 18, 2010
Where: Joint IAPR International Conference on Structural, Syntactic and Statistical Pattern Recognition (SSPR & SPR)
Research Area: Machine Learning
Brief - The paper "Learning on Manifolds" by Porikli, F. was presented at the Joint IAPR International Conference on Structural, Syntactic and Statistical Pattern Recognition (SSPR & SPR).
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- Date: June 13, 2010
Where: IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum
Research Area: Machine Learning
Brief - The paper "RelCom: Relational Combinatorics Features for Rapid Object Detection" by Venkatraman, V. and Porikli, F.M. was presented at the IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum.
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- Date: June 1, 2010
Awarded to: Vijay Venkataraman and Fatih Porikli
Awarded for: "RelCom: Relational Combinatorics Features for Rapid Object Detection"
Awarded by: IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum (OTCBVS)
Research Area: Machine Learning
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- Date: October 3, 2009
Where: On-line Learning for Computer Vision Workshop (OLCV)
MERL Contact: Michael J. Jones
Research Area: Machine Learning
Brief - The paper "Online Coordinate Boosting" by Pelossof, R., Jones, M.J., Vovsha, I. and Rudin, C. was presented at the On-line Learning for Computer Vision Workshop (OLCV).
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- Date: September 29, 2009
Where: IEEE International Conference on Computer Vision (ICCV)
Research Area: Machine Learning
Brief - The paper "Kernel Methods for Weakly Supervised Mean Shift Clustering" by Tuzel, C.O., Porikli, F.M. and Meer, P. was presented at the IEEE International Conference on Computer Vision (ICCV).
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- Date: September 2, 2009
Where: IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
Research Area: Machine Learning
Brief - The paper "Regressed Importance Sampling on Manifolds for Efficient Object Tracking" by Porikli, F.M. and Pan, P. was presented at the IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).
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- Date: September 1, 2009
Where: IEEE Transactions on Intelligent Transportation Systems
Research Area: Machine Learning
Brief - The article "A Comprehensive Evaluation Framework and a Comparative Study for Human Detectors" by Hussein, M.E., Porikli, F.M. and Davis, L. was published in IEEE Transactions on Intelligent Transportation Systems.
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- Date: May 20, 2009
Where: IAPR Conference on Machine vision Applications (MVA)
Research Area: Machine Learning
Brief - The paper "A New Approach for In-Vehicle Camera Traffic Sign Detection and Recognition" by Ruta, A., Porikli, F., Li, Y., Watanabe, S., Kage, H. and Sumi, K. was presented at the IAPR Conference on Machine vision Applications (MVA).
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- Date: January 15, 2009
Where: IEEJ Transactions on Electronic, Information and Systems
MERL Contact: Michael J. Jones
Research Area: Machine Learning
Brief - The article "Face Recognition: Where we are and where to go from here" by Jones, M.J. was published in IEEJ Transactions on Electronic, Information and Systems.
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- Date: December 8, 2008
Where: IEEE International Conference on Pattern Recognition (ICPR)
MERL Contact: Michael J. Jones
Research Area: Machine Learning
Brief - The paper "Pedestrian Detection Using Boosted Features Over Many Frames" by Jones, M. and Snow, D. was presented at the IEEE International Conference on Pattern Recognition (ICPR).
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- Date: October 15, 2008
Where: IEEE Transactions on Pattern Analysis and Machine Intelligence
Research Area: Machine Learning
Brief - The article "Pedestrian Detection via Classification on Riemannian Manifolds" by Tuzel, O., Porikli, F. and Meer, P. was published in IEEE Transactions on Pattern Analysis and Machine Intelligence.
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- Date: May 19, 2008
Where: IEEE Workshop on Human Detection from Mobile Platforms
Research Area: Machine Learning
Brief - The paper "Towards Practical Evaluation of Pedestrian Detectors" by Hussein, M., Porikli, F. and Davis, L. was presented at the IEEE Workshop on Human Detection from Mobile Platforms.
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- Date: August 1, 2007
Where: Journal of Computers
Research Area: Machine Learning
Brief - The article "Integrated Detection, Tracking and Recognition for IR Video-based Vehicle Classification" by Mei, X., Zhou, S.K., Wu, H. and Porikli, F. was published in Journal of Computers.
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