Researcher

Mark Finocchio

Also known as M. Finocchio

Mark Finocchio is a computer-vision researcher whose coauthored pose-recognition work helped bring real-time body tracking to Kinect. In September 2008, he asked Microsoft Research for help with a planned game accessory that could track bodies; in June 2011, he coauthored a CVPR method to predict 3D body joints from one depth image, which won CVPR’s Best Paper Award. He also coauthored a 2011 paper on parallelizing Kinect’s body-parts classifier. His patents cover an on-demand property system and machine-learning classifier training, and CVPR’s 2021 Longuet-Higgins Prize recognizes the pose paper.

Timeline

  1. 2002–2006

    An on-demand property system

    In 2002, he files a Microsoft patent for an on-demand property system that tracks dependencies among object properties; the patent is granted in 2006.

  2. September 2008

    Starting Kinect body tracking

    In September 2008, he emails Microsoft Research’s Jamie Shotton to ask for help with a planned game accessory that can track bodies in real time. He is a principal software engineer with Microsoft’s Interactive Entertainment Business.

  3. 2011

    Recognizing pose from depth

    At CVPR in June 2011, he coauthors a method that predicts 3D body-joint positions from one depth image by classifying pixels into body parts. The system runs at 200 frames per second on consumer hardware.

  4. 2011

    A CVPR Best Paper Award

    The human-pose paper wins CVPR’s Best Paper Award during the 2011 conference.

  5. 2011

    Parallelizing Kinect training

    In December 2011, he coauthors a paper on parallelizing the decision-forest training used for Kinect’s body-parts classification system.

  6. 2016

    Partitioning training data

    A 2016 patent names him as a co-inventor of a method that uses a global classifier to partition training data into class-specific subsets, then trains a second classifier on those subsets.

  7. 2021

    The Longuet-Higgins Prize

    CVPR’s 2021 Longuet-Higgins Prize recognizes the 2011 human-pose paper he coauthors.

Sources and credits

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  1. US6986123B2 - Extensible on-demand property system patents.google.com. Checked 21 October 2026.
  2. Kinect Body Tracking Reaps Renown microsoft.com. Checked 21 October 2026.
  3. Real-Time Human Pose Recognition in Parts from a Single Depth Image microsoft.com. Checked 21 October 2026.
  4. Parallelizing the Training of the Kinect Body Parts Labeling Algorithm microsoft.com. Checked 21 October 2026.
  5. US20160132786A1 - Partitioning data for training machine-learning classifiers patents.google.com. Checked 21 October 2026.
  6. PAMITC AWARDS | CVPR 2021 cvpr2021.thecvf.com. Checked 21 October 2026.