Computational Sensing

Utilizing computation to improve sensing capabilities.

Our research in the area of computational sensing focuses on signal acquisition and design, signal modeling and reconstruction algorithms, including inverse problems, as well as array signal processing techniques.

  • Researchers

  • Awards

    •  AWARD   2015 IEEE Signal Processing Society Best Paper Award
      Date: December 1, 2015
      Awarded to: Mark A. Davenport, Petros T. Boufounos, Michael B. Wakin and Richard G. Baraniuk
      MERL Contact: Petros Boufounos
      Research Area: Computational Sensing
      Brief
      • Petros Boufounos is a recipient of the 2015 IEEE Signal Processing Society Best Paper Award for the paper that he co-authored with Mark A. Davenport, Michael B. Wakin and Richard G. Baraniuk on "Signal Processing with Compressive Measurements" which was published in the April 2010 issue of IEEE Journal of Selected Topics in Signal Processing. The Best Paper Award honors the author(s) of a paper of exceptional merit dealing with a subject related to the Society's technical scope, and appearing in one of the Society's solely owned transactions or the Journal of Selected Topics in Signal Processing. Eligibility is based on a five-year window: for example, for the 2015 Award, the paper must have appeared in one of the Society's Transactions between January 1, 2010 and December 31, 2014.
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    •  AWARD   GRSS 2014 Symposium Prize Paper Award
      Date: May 1, 2014
      Awarded to: Dehong Liu and Petros T. Boufounos
      Awarded for: "Synthetic Aperture Imaging Using a Randomly Steered Spotlight"
      Awarded by: IEEE Geoscience and Remote Sensing Society (GRSS)
      MERL Contacts: Dehong Liu; Petros Boufounos
      Research Area: Computational Sensing
      Brief
      • Dehong Liu and Petros T. Boufounos are the recipients of the the IEEE Geoscience and Remote Sensing Society 2014 Symposium Prize Paper Award for their paper "Synthetic Aperture Imaging Using a Randomly Steered Spotlight," presented at IGARSS 2013 (TR2013-070).
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    •  AWARD   MMSP 2012 Top 10% Paper Award
      Date: September 1, 2012
      Awarded to: Mu Li, Shantanu Rane and Petros Boufounos
      Awarded for: "Quantized Embeddings of Scale-Invariant Image Features for Mobile Augmented Reality"
      Awarded by: IEEE International Workshop on Multimedia Signal Processing (MMSP)
      MERL Contact: Petros Boufounos
      Research Areas: Digital Video, Computational Sensing
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  • News & Events

    •  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   IEEE-NH ComSig lecture by MERL's Petros Boufounos
      Date: April 4, 2019
      Where: Nashua Public Library, Nashua, NH
      MERL Contact: Petros Boufounos
      Research Areas: Computational Sensing, Signal Processing
      Brief
      • MERL's Petros Boufounos gave a lecture for the IEEE-NH ComSig chapter at the Nashua Public Library as part of the IEEE Signal Processing Society Distinguished Lecturer series.

        Title: "An Inverse Problem Framework for Array Processing Systems."

        Abstract: Array-based sensing systems, such as ultrasonic, radar and optical (LIDAR) are becoming increasingly important in a variety of applications, including robotics, autonomous driving, medical imaging, and virtual reality, among others. This has led to continuous improvements in sensing hardware, but also to increasing demand for theory and methods to inform the system design and improve the processing. In this talk we will discuss how recent advances in formulating and solving inverse problems, such as compressed sensing, blind deconvolution, and sparse signal modeling can be applied to significantly reduce the cost and improve the capabilities of array-based and multichannel sensing systems. We show that these systems share a common mathematical framework, which allows us to describe both the acquisition hardware and the scene being acquired. Under this framework we can exploit prior knowledge on the scene, the system, and a variety of errors that might occur, allowing for significant improvements in the reconstruction accuracy. Furthermore, we can consider the design of the system itself in the context of the inverse problem, leading to designs that are more efficient, more accurate, or less expensive, depending on the application. In the talk we will explore applications of this model to LIDAR and depth sensing, radar and distributed radar, and ultrasonic sensing. In the context of these applications, we will describe how different models can lead to improved specifications in ultrasonic systems, robustness to position and timing errors in distributed array systems, and cost reduction and new capabilities in LIDAR systems.
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  • Research Highlights

  • Internships

    • SP1424: Advanced computational sensing technologies

      The Computational Sensing team at MERL is seeking motivated and qualified individuals to develop computational imaging algorithms for a variety of sensing applications. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, learning for inverse problems, large-scale optimization, blind inverse scattering, radar/lidar/sonar imaging, or wave-based inversion. Experience with experimentally measured data is desirable. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible.

    • MD1398: Electrical machine modeling

      MERL is looking for a self-motivated intern to work on electrical machine modelling and signal processing. The ideal candidate would be a Ph.D. candidate in electrical engineering with solid research background in electrical machines, signal processing, and electrical circuit analysis. Experience in transient analysis of electrical machines is desirable. Proficiency in MATLAB and simulink is necessary. The intern is expected to collaborate with MERL researchers to build models, develop algorithms, and prepare manuscripts for scientific publications. The total duration is 3 months.


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  • Recent Publications

    •  Ma, Y., Lodhi, M.A., Mansour, H., Boufounos, P.T., Liu, D., "Inverse Multiple Scattering With Phaseless Measurements", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053430, April 2020, pp. 1519-1523.
      BibTeX TR2020-041 PDF Video
      • @inproceedings{Ma2020apr,
      • author = {Ma, Yanting and Lodhi, Muhammad Asad and Mansour, Hassan and Boufounos, Petros T. and Liu, Dehong},
      • title = {Inverse Multiple Scattering With Phaseless Measurements},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2020,
      • pages = {1519--1523},
      • month = apr,
      • publisher = {IEEE},
      • doi = {10.1109/ICASSP40776.2020.9053430},
      • issn = {2379-190X},
      • isbn = {978-1-5090-6631-5},
      • url = {https://www.merl.com/publications/TR2020-041}
      • }
    •  Wang, P., Boufounos, P.T., Mansour, H., Orlik, P.V., "Slow-Time MIMO-FMCW Automotive Radar Detection with Imperfect Waveform Separation", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053892, April 2020, pp. 8634-8638.
      BibTeX TR2020-039 PDF Video
      • @inproceedings{Wang2020apr,
      • author = {Wang, Pu and Boufounos, Petros T. and Mansour, Hassan and Orlik, Philip V.},
      • title = {Slow-Time MIMO-FMCW Automotive Radar Detection with Imperfect Waveform Separation},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2020,
      • pages = {8634--8638},
      • month = apr,
      • publisher = {IEEE},
      • doi = {10.1109/ICASSP40776.2020.9053892},
      • issn = {2379-190X},
      • isbn = {978-1-5090-6631-5},
      • url = {https://www.merl.com/publications/TR2020-039}
      • }
    •  Xia, Y., Wang, P., Berntorp, K., Koike-Akino, T., Mansour, H., Pajovic, M., Boufounos, P.T., Orlik, P.V., "Extended Object Tracking Using Hierarchical Truncation Measurement Model with Automotive Radar", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9054614, April 2020, pp. 4900-4904.
      BibTeX TR2020-044 PDF Video
      • @inproceedings{Xia2020apr,
      • author = {Xia, Yuxuan and Wang, Pu and Berntorp, Karl and Koike-Akino, Toshiaki and Mansour, Hassan and Pajovic, Milutin and Boufounos, Petros T. and Orlik, Philip V.},
      • title = {Extended Object Tracking Using Hierarchical Truncation Measurement Model with Automotive Radar},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2020,
      • pages = {4900--4904},
      • month = apr,
      • publisher = {IEEE},
      • doi = {10.1109/ICASSP40776.2020.9054614},
      • issn = {2379-190X},
      • isbn = {978-1-5090-6631-5},
      • url = {https://www.merl.com/publications/TR2020-044}
      • }
    •  Xie, Y., Liu, D., Mansour, H., Boufounos, P.T., "Robust Parameter Estimation of Contaminated Damped Exponentials", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053507, April 2020, pp. 5500-5504.
      BibTeX TR2020-052 PDF Video
      • @inproceedings{Xie2020apr,
      • author = {Xie, Youye and Liu, Dehong and Mansour, Hassan and Boufounos, Petros T.},
      • title = {Robust Parameter Estimation of Contaminated Damped Exponentials},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2020,
      • pages = {5500--5504},
      • month = apr,
      • publisher = {IEEE},
      • doi = {10.1109/ICASSP40776.2020.9053507},
      • issn = {2379-190X},
      • isbn = {978-1-5090-6631-5},
      • url = {https://www.merl.com/publications/TR2020-052}
      • }
    •  Yu, L., Liu, D., Mansour, H., Boufounos, P.T., Ma, Y., "Blind Multi-Spectral Image Pan-Sharpening", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053554, April 2020, pp. 1429-1433.
      BibTeX TR2020-047 PDF Video
      • @inproceedings{Yu2020apr,
      • author = {Yu, Lantao and Liu, Dehong and Mansour, Hassan and Boufounos, Petros T. and Ma, Yanting},
      • title = {Blind Multi-Spectral Image Pan-Sharpening},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2020,
      • pages = {1429--1433},
      • month = apr,
      • publisher = {IEEE},
      • doi = {10.1109/ICASSP40776.2020.9053554},
      • issn = {2379-190X},
      • isbn = {978-1-5090-6631-5},
      • url = {https://www.merl.com/publications/TR2020-047}
      • }
    •  Wang, P., Li, H., "Target Detection with Imperfect Waveform Separation in Distributed MIMO Radar", IEEE Transactions on Signal Processing, DOI: 10.1109/TSP.2020.2964227, Vol. 68, No. 1, pp. 793-807, January 2020.
      BibTeX TR2020-007 PDF
      • @article{Wang2020jan,
      • author = {Wang, Pu and Li, Hongbin},
      • title = {Target Detection with Imperfect Waveform Separation in Distributed MIMO Radar},
      • journal = {IEEE Transactions on Signal Processing},
      • year = 2020,
      • volume = 68,
      • number = 1,
      • pages = {793--807},
      • month = jan,
      • doi = {10.1109/TSP.2020.2964227},
      • issn = {1053-587X},
      • url = {https://www.merl.com/publications/TR2020-007}
      • }
    •  Pajovic, M., Wang, P., Koike-Akino, T., Sun, H., Orlik, P.V., "Fingerprinting-Based Indoor Localization with Commercial MMWave WiFi - Part I: RSS and Beam Indices", IEEE Global Communications Conference (GLOBECOM), DOI: 10.1109/GLOBECOM38437.2019.9013466, December 2019.
      BibTeX TR2019-141 PDF Data
      • @inproceedings{Pajovic2019dec,
      • author = {Pajovic, Milutin and Wang, Pu and Koike-Akino, Toshiaki and Sun, Haijian and Orlik, Philip V.},
      • title = {Fingerprinting-Based Indoor Localization with Commercial MMWave WiFi - Part I: RSS and Beam Indices},
      • booktitle = {IEEE Global Communications Conference (GLOBECOM)},
      • year = 2019,
      • month = dec,
      • publisher = {IEEE},
      • doi = {10.1109/GLOBECOM38437.2019.9013466},
      • issn = {2576-6813},
      • isbn = {978-1-7281-0962-6},
      • url = {https://www.merl.com/publications/TR2019-141}
      • }
    •  Kao, J.-Y., Ortega, A., Tian, D., Mansour, H., Vetro, A., "Graph Based Skeleton Modeling for Human Activity Analysis", IEEE International Conference on Image Processing (ICIP), DOI: 10.1109/ICIP.2019.8803186, September 2019.
      BibTeX TR2019-037 PDF
      • @inproceedings{Kao2019sep,
      • author = {Kao, Jiun-Yu and Ortega, Antonio and Tian, Dong and Mansour, Hassan and Vetro, Anthony},
      • title = {Graph Based Skeleton Modeling for Human Activity Analysis},
      • booktitle = {IEEE International Conference on Image Processing (ICIP)},
      • year = 2019,
      • month = sep,
      • publisher = {IEEE},
      • doi = {10.1109/ICIP.2019.8803186},
      • issn = {2381-8549},
      • isbn = {978-1-5386-6249-6},
      • url = {https://www.merl.com/publications/TR2019-037}
      • }
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  • Videos