People - Michael Jones | Mitsubishi Electric Research Laboratories

Biography

Mike's main areas of interest are computer vision, machine learning and data mining. He has focused on algorithms for detecting and analyzing people in images and video including face detection and recognition and pedestrian detection. He is a co-inventor of the popular Viola-Jones face detection method. Mike has been awarded the Marr Prize at ICCV and the Longuet-Higgins Prize at CVPR.
Recent News & Events
- 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.
- 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%.
See All News & Events for Mike
Awards
- AWARD CVPR 2011 Longuet-Higgins Prize
  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 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).
See All Awards for MERL
Research Highlights
- MERL Shopping Dataset
- Video Anomaly Detection
MERL Publications
- Jones, M.J., Ramachandra, B., Vatsavai, R., "A Survey of Single-Scene Video Anomaly Detection", arXiv, August 2020.
  BibTeX
  - @article{Jones2020aug,
  - author = {Jones, Michael J. and Ramachandra, Bharathkumar and Vatsavai, Ranga},
  - title = {A Survey of Single-Scene Video Anomaly Detection},
  - journal = {arXiv},
  - year = 2020,
  - month = aug
  - }
- Kumar, A., Marks, T., Mou, W., Wang, Y., Cherian, A., Jones, M.J., Liu, X., Koike-Akino, T., Feng, C., "LUVLi Face Alignment: Estimating Landmarks’ Location, Uncertainty, and Visibility Likelihood", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2020.
  BibTeX TR2020-067 PDF Video Data
  - @inproceedings{Kumar2020jun,
  - author = {Kumar, Abhinav and Marks, Tim and Mou, Wenxuan and Wang, Ye and Cherian, Anoop and Jones, Michael J. and Liu, Xiaoming and Koike-Akino, Toshiaki and Feng, Chen},
  - title = {LUVLi Face Alignment: Estimating Landmarks’ Location, Uncertainty, and Visibility Likelihood},
  - booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  - year = 2020,
  - month = jun,
  - url = {https://www.merl.com/publications/TR2020-067}
  - }
- Ramachandra, B., Jones, M.J., Vatsavai, R., "A Survey of Single-Scene Video Anomaly Detection", arXiv, April 2020.
  BibTeX arXiv
  - @article{Ramachandra2020apr,
  - author = {Ramachandra, Bharathkumar and Jones, Michael J. and Vatsavai, Ranga},
  - title = {A Survey of Single-Scene Video Anomaly Detection},
  - journal = {arXiv},
  - year = 2020,
  - month = apr,
  - url = {https://arxiv.org/abs/2004.05993}
  - }
- Ramachandra, B., Jones, M.J., "Street Scene: A new dataset and evaluation protocol for video anomaly detection", IEEE Winter Conference on Applications of Computer Vision (WACV), DOI: 10.1109/WACV45572.2020.9093457, February 2020, pp. 2569-2578.
  BibTeX TR2020-017 PDF Data
  - @inproceedings{Jones2020feb2,
  - author = {Ramachandra, Bharathkumar and Jones, Michael J.},
  - title = {Street Scene: A new dataset and evaluation protocol for video anomaly detection},
  - booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)},
  - year = 2020,
  - pages = {2569--2578},
  - month = feb,
  - doi = {10.1109/WACV45572.2020.9093457},
  - url = {https://www.merl.com/publications/TR2020-017}
  - }
- Ramachandra, B., Jones, M.J., Vatsavai, R., "Learning a distance function with a Siamese network to localize anomalies in videos", IEEE Winter Conference on Applications of Computer Vision (WACV), DOI: 10.1109/WACV45572.2020.9093417, February 2020, pp. 2598-2607.
  BibTeX TR2020-015 PDF
  - @inproceedings{Jones2020feb,
  - author = {Ramachandra, Bharathkumar and Jones, Michael J. and Vatsavai, Ranga},
  - title = {Learning a distance function with a Siamese network to localize anomalies in videos},
  - booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)},
  - year = 2020,
  - pages = {2598--2607},
  - month = feb,
  - doi = {10.1109/WACV45572.2020.9093417},
  - url = {https://www.merl.com/publications/TR2020-015}
  - }
See All Publications for Mike
Other Publications
- G.B. Huang, M.J. Jones, E. Learned-Miller and others, "Lfw results using a combined nowak plus merl recognizer", 2008.
  BibTeX
  - @Article{huang2008lfw,
  - author = {Huang, G.B. and Jones, M.J. and Learned-Miller, E. and others},
  - title = {Lfw results using a combined nowak plus merl recognizer},
  - year = 2008
  - }
- T.J. Cham, S. Krishnamoorthy and M. Jones, "Analogous view transfer for gaze correction in video sequences", Control, Automation, Robotics and Vision, 2002. ICARCV 2002. 7th International Conference on, 2002, vol. 3, pp. 1415-1420.
  BibTeX
  - @Inproceedings{cham2002analogous,
  - author = {Cham, T.J. and Krishnamoorthy, S. and Jones, M.},
  - title = {Analogous view transfer for gaze correction in video sequences},
  - booktitle = {Control, Automation, Robotics and Vision, 2002. ICARCV 2002. 7th International Conference on},
  - year = 2002,
  - volume = 3,
  - pages = {1415--1420},
  - organization = {IEEE}
  - }
- M.J. Jones and J.M. Rehg, "Statistical color models with application to skin detection", International Journal of Computer Vision, Vol. 46, No. 1, pp. 81-96, 2002.
  BibTeX
  - @Article{jones2002statistical,
  - author = {Jones, M.J. and Rehg, J.M.},
  - title = {Statistical color models with application to skin detection},
  - journal = {International Journal of Computer Vision},
  - year = 2002,
  - volume = 46,
  - number = 1,
  - pages = {81--96},
  - publisher = {Springer}
  - }
- S.B. Kang and M. Jones, "Appearance-based structure from motion using linear classes of 3-d models", International Journal of Computer Vision, Vol. 49, No. 1, pp. 5-22, 2002.
  BibTeX
  - @Article{kang2002appearance,
  - author = {Kang, S.B. and Jones, M.},
  - title = {Appearance-based structure from motion using linear classes of 3-d models},
  - journal = {International Journal of Computer Vision},
  - year = 2002,
  - volume = 49,
  - number = 1,
  - pages = {5--22},
  - publisher = {Springer}
  - }
- C.M. Procopiuc, M. Jones, P.K. Agarwal and TM Murali, "A Monte Carlo algorithm for fast projective clustering", Proceedings of the 2002 ACM SIGMOD international conference on Management of data, 2002, pp. 418-427.
  BibTeX
  - @Inproceedings{procopiuc2002monte,
  - author = {Procopiuc, C.M. and Jones, M. and Agarwal, P.K. and Murali, TM},
  - title = {A Monte Carlo algorithm for fast projective clustering},
  - booktitle = {Proceedings of the 2002 ACM SIGMOD international conference on Management of data},
  - year = 2002,
  - pages = {418--427},
  - organization = {ACM}
  - }
- P. Viola and M. Jones, "Fast and robust classification using asymmetric adaboost and a detector cascade", Proc. of NIPS01, 2001.
  BibTeX
  - @Article{viola2001fast,
  - author = {Viola, P. and Jones, M.},
  - title = {Fast and robust classification using asymmetric adaboost and a detector cascade},
  - journal = {Proc. of NIPS01},
  - year = 2001
  - }
- M.J. Jones and J.M. Rehg, "Statistical color models with application to skin detection", Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on., 1999, vol. 1.
  BibTeX
  - @Inproceedings{jones1999statistical,
  - author = {Jones, M.J. and Rehg, J.M.},
  - title = {Statistical color models with application to skin detection},
  - booktitle = {Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on.},
  - year = 1999,
  - volume = 1,
  - organization = {IEEE}
  - }
- T.D. Rikert, M.J. Jones and P. Viola, "A cluster-based statistical model for object detection", Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on, 1999, vol. 2, pp. 1046-1053.
  BibTeX
  - @Inproceedings{rikert1999cluster,
  - author = {Rikert, T.D. and Jones, M.J. and Viola, P.},
  - title = {A cluster-based statistical model for object detection},
  - booktitle = {Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on},
  - year = 1999,
  - volume = 2,
  - pages = {1046--1053},
  - organization = {IEEE}
  - }
- M.J. Jones and T. Poggio, "Hierarchical morphable models", Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on, 1998, pp. 820-826.
  BibTeX
  - @Inproceedings{jones1998hierarchical,
  - author = {Jones, M.J. and Poggio, T.},
  - title = {Hierarchical morphable models},
  - booktitle = {Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on},
  - year = 1998,
  - pages = {820--826},
  - organization = {IEEE}
  - }
- M.J. Jones and T. Poggio, "Multidimensional morphable models: A framework for representing and matching object classes", International Journal of Computer Vision, Vol. 29, No. 2, pp. 107-131, 1998.
  BibTeX
  - @Article{jones1998multidimensional,
  - author = {Jones, M.J. and Poggio, T.},
  - title = {Multidimensional morphable models: A framework for representing and matching object classes},
  - journal = {International Journal of Computer Vision},
  - year = 1998,
  - volume = 29,
  - number = 2,
  - pages = {107--131},
  - publisher = {Springer}
  - }
- T.D. Rikert and M.J. Jones, "Gaze estimation using morphable models", Automatic Face and Gesture Recognition, 1998. Proceedings. Third IEEE International Conference on, 1998, pp. 436-441.
  BibTeX
  - @Inproceedings{rikert1998gaze,
  - author = {Rikert, T.D. and Jones, M.J.},
  - title = {Gaze estimation using morphable models},
  - booktitle = {Automatic Face and Gesture Recognition, 1998. Proceedings. Third IEEE International Conference on},
  - year = 1998,
  - pages = {436--441},
  - organization = {IEEE}
  - }
- M.J. Jones, "Multidimensional morphable models: A framework for representing and matching object classes", 1997.
  BibTeX
  - @Phdthesis{jones1997multidimensional,
  - author = {Jones, M.J.},
  - title = {Multidimensional morphable models: A framework for representing and matching object classes},
  - year = 1997,
  - publisher = {Massachusetts Institute of Technology}
  - }
- M.J. Jones, P. Sinha, T. Vetter and T. Poggio, "Top-down learning of low-level vision tasks", Current Biology, Vol. 7, No. 12, pp. 991-994, 1997.
  BibTeX
  - @Article{jones1997top,
  - author = {Jones, M.J. and Sinha, P. and Vetter, T. and Poggio, T.},
  - title = {Top-down learning of low-level vision tasks},
  - journal = {Current Biology},
  - year = 1997,
  - volume = 7,
  - number = 12,
  - pages = {991--994},
  - publisher = {Elsevier}
  - }
- T. Vetter, M.J. Jones and T. Poggio, "A bootstrapping algorithm for learning linear models of object classes", Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on, 1997, pp. 40-46.
  BibTeX
  - @Inproceedings{vetter1997bootstrapping,
  - author = {Vetter, T. and Jones, M.J. and Poggio, T.},
  - title = {A bootstrapping algorithm for learning linear models of object classes},
  - booktitle = {Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on},
  - year = 1997,
  - pages = {40--46},
  - organization = {IEEE}
  - }
- F. Girosi, M. Jones and T. Poggio, "Regularization theory and neural networks architectures", Neural computation, Vol. 7, No. 2, pp. 219-269, 1995.
  BibTeX
  - @Article{girosi1995regularization,
  - author = {Girosi, F. and Jones, M. and Poggio, T.},
  - title = {Regularization theory and neural networks architectures},
  - journal = {Neural computation},
  - year = 1995,
  - volume = 7,
  - number = 2,
  - pages = {219--269},
  - publisher = {MIT Press}
  - }
- M.J. Jones and T. Poggio, "Model-based matching of line drawings by linear combinations of prototypes", Computer Vision, 1995. Proceedings., Fifth International Conference on, 1995, pp. 531-536.
  BibTeX
  - @Inproceedings{jones1995model,
  - author = {Jones, M.J. and Poggio, T.},
  - title = {Model-based matching of line drawings by linear combinations of prototypes},
  - booktitle = {Computer Vision, 1995. Proceedings., Fifth International Conference on},
  - year = 1995,
  - pages = {531--536},
  - organization = {IEEE}
  - }
- F. Girosi, M. Jones and T. Poggio, "Priors stabilizers and basis functions: From regularization to radial, tensor and additive splines", MIT AI Lab Memo 1430, 1993.
  BibTeX
  - @Article{girosi1993priors,
  - author = {Girosi, F. and Jones, M. and Poggio, T.},
  - title = {Priors stabilizers and basis functions: From regularization to radial, tensor and additive splines},
  - journal = {MIT AI Lab Memo 1430},
  - year = 1993
  - }
- T. Poggio, F. Girosi and M. Jones, "From regularization to radial, tensor and additive splines", Neural Networks, 1993. IJCNN'93-Nagoya. Proceedings of 1993 International Joint Conference on, 1993, vol. 1, pp. 223-227.
  BibTeX
  - @Inproceedings{poggio1993regularization,
  - author = {Poggio, T. and Girosi, F. and Jones, M.},
  - title = {From regularization to radial, tensor and additive splines},
  - booktitle = {Neural Networks, 1993. IJCNN'93-Nagoya. Proceedings of 1993 International Joint Conference on},
  - year = 1993,
  - volume = 1,
  - pages = {223--227},
  - organization = {IEEE}
  - }
- M.J. Jones, "Using recurrent networks for dimensionality reduction", 1992, Massachusetts Institute of Technology.
  BibTeX
  - @Mastersthesis{jones1992using,
  - author = {Jones, M.J.},
  - title = {Using recurrent networks for dimensionality reduction},
  - school = {Massachusetts Institute of Technology},
  - year = 1992
  - }
Software Downloads
- Exemplar-Based Anomaly Detection
Videos
- Action Detection Using A Deep Recurrent Neural Network
MERL Issued Patents
- Title: "System and Method for Detecting Anomalies in Video using a Similarity Function Trained by Machine Learning"
  Inventors: Jones, Michael J.
  Patent No.: 10,824,935
  Issue Date: Nov 3, 2020
- Title: "Method and System for Determining 3D Object Poses and Landmark Points using Surface Patches"
  Inventors: Jones, Michael J.; Marks, Tim; Papazov, Chavdar
  Patent No.: 10,515,259
  Issue Date: Dec 24, 2019
- Title: "System and Method for Image Comparison Based on Hyperplanes Similarity"
  Inventors: Jones, Michael J.
  Patent No.: 10,452,958
  Issue Date: Oct 22, 2019
- Title: "Method and System for Detecting Actions in Videos"
  Inventors: Jones, Michael J.; Tuzel, Oncel; Marks, Tim; Singh, Bharat
  Patent No.: 10,242,266
  Issue Date: Mar 26, 2019
- Title: "Method and System for Detecting Actions in Videos using Contour Sequences"
  Inventors: Jones, Michael J.; Marks, Tim; Kulkarni, Kuldeep
  Patent No.: 10,210,391
  Issue Date: Feb 19, 2019
- Title: "Method for Anomaly Detection in Time Series Data Based on Spectral Partitioning"
  Inventors: Nikovski, Daniel N.; Kniazev, Andrei; Jones, Michael J.
  Patent No.: 9,984,334
  Issue Date: May 29, 2018
- Title: "Method for Learning Exemplars for Anomaly Detection"
  Inventors: Jones, Michael J.; Nikovski, Daniel N.
  Patent No.: 9,779,361
  Issue Date: Oct 3, 2017
- Title: "Method for Determining Similarity of Objects Represented in Images"
  Inventors: Jones, Michael J.; Marks, Tim; Ahmed, Ejaz
  Patent No.: 9,436,895
  Issue Date: Sep 6, 2016
- Title: "Method and System for Tracking People in Indoor Environments using a Visible Light Camera and a Low-Frame-Rate Infrared Sensor"
  Inventors: Marks, Tim; Jones, Michael J.; Kumar, Suren
  Patent No.: 9,245,196
  Issue Date: Jan 26, 2016
- Title: "Method for Detecting and Tracking Objects in Image Sequences of Scenes Acquired by a Stationary Camera"
  Inventors: Marks, Tim; Jones, Michael J.; MV, Rohith
  Patent No.: 9,213,896
  Issue Date: Dec 15, 2015
- Title: "Method for Detecting Anomalies in a Time Series Data with Trajectory and Stochastic Components"
  Inventors: Jones, Michael J.
  Patent No.: 9,146,800
  Issue Date: Sep 29, 2015
- Title: "Method for Predicting Future Travel Time Using Geospatial Inference"
  Inventors: Jones, Michael J.; Nikovski, Daniel N.; Geng, Yanfeng
  Patent No.: 9,122,987
  Issue Date: Sep 1, 2015
- Title: "Method for Detecting Anomalies in Multivariate Time Series Data"
  Inventors: Nikovski, Daniel N.; Jones, Michael J.
  Patent No.: 9,075,713
  Issue Date: Jul 7, 2015
- Title: "Camera-Based 3D Climate Control"
  Inventors: Marks, Tim; Jones, Michael J.
  Patent No.: 8,929,592
  Issue Date: Jan 6, 2015
- Title: "Object Detection in Depth Images"
  Inventors: Jones, Michael J.; Tuzel, C. Oncel; Si, Weiguang
  Patent No.: 8,406,470
  Issue Date: Mar 26, 2013
- Title: "Method for identifying Faces in Images with Improved Accuracy Using Compressed Feature Vectors"
  Inventors: Thornton, Jay E.; Jones, Michael J.
  Patent No.: 8,213,691
  Issue Date: Jul 3, 2012
- Title: "Method for Synthetically Images of Objects"
  Inventors: Jones, Michael J.; Marks, Tim; Kumar, Ritwik
  Patent No.: 8,194,072
  Issue Date: Jun 5, 2012
- Title: "Method for Localizing Irises in Images Using Gradients and Textures"
  Inventors: Jones, Michael J.; Guo, Guo Dong
  Patent No.: 7,583,823
  Issue Date: Sep 1, 2009
- Title: "Detecting Pedestrians Using Patterns of Motion and Appearance in Videos"
  Inventors: Jones, Michael J.; Viola, Paul A.
  Patent No.: 7,212,651
  Issue Date: May 1, 2007
- Title: "Detecting Arbitrarily Oriented Objects in Images"
  Inventors: Viola, Paul A.; Jones, Michael J.
  Patent No.: 7,197,186
  Issue Date: Mar 27, 2007
- Title: "Object Recognition System"
  Inventors: Viola, Paul A.; Jones, Michael J.
  Patent No.: 7,031,499
  Issue Date: Apr 18, 2006
- Title: "System and Method for Detecting Objects in Images"
  Inventors: Viola, Paul A.; Jones, Michael J.
  Patent No.: 7,020,337
  Issue Date: Mar 28, 2006
See All Patents for MERL

Mitsubishi Electric | Changes for the Better MERL - Mitsubishi Electric Research Laboratories

Michael Jones

Position:

Education:

Research Areas:

External Links:

Mike's Quick Links

Biography

Recent News & Events

Awards

Research Highlights

MERL Shopping Dataset

Video Anomaly Detection

MERL Publications

Other Publications

Software Downloads

Exemplar-Based Anomaly Detection

Videos

MERL Issued Patents

MERL Shopping Dataset

Video Anomaly Detection

Exemplar-Based Anomaly Detection

Action Detection Using A Deep Recurrent Neural Network