Keith Fieldhouse

Keith Fieldhouse

Assistant Director of Computer Vision

Keith joined Kitware in May 2010 as a Research and Development engineer and was rapidly promoted to Technical Lead for his technical contributions and leadership across multiple projects in the Computer Vision Group, particularly the DARPA PerSEAS and VIRAT efforts. Keith continues to provide technical and project leadership on multiple efforts, such as the Air Force Research Laboratory’s Data-To-Decisions program. Keith specializes in large system design and integration, including field tests and transition to operational use.

Previously, Keith worked for IBM, Digital Equipment Corporation, and as an independent consultant building medical software for Apple Macintosh computers. He then took a position with Adobe Systems in Seattle, Washington, where he pioneered Adobe’s early online commerce activities and joined the Consumer Systems Group dedicated to bringing Adobe technology to non-traditional consumer computing devices. The Consumer Systems Group was spun out by Adobe as PictureIQ Inc. where Keith served as the head of engineering, architecting and developing award winning server technology for the then nascent online photo industry. Keith Fieldhouse graduated with a B.S. in Computer Science from the Rochester Institute of Technology.

More recently Keith worked at Simmetrix Inc, where he was the lead and principal architect of a Python-based rapid development environment for Simulation Based Design.

  1. S. Han et al., "Efficient generation of image chips for training deep learning algorithms," in SPIE Defense + Security, Anaheim, California, United States, 2017.
  2. M. Dawkins et al., "An open-source platform for underwater image and video analytics," in IEEE Winter Conference on Applications of Computer Vision (WACV), Santa Rosa, CA, USA, 2017.
  3. M. Turek et al., "Real-time, full-frame wide area motion imagery analytics," in Military Sensing Symposia - Passive Sensors, 2015.
  4. A. Hoogs et al., "An end-to-end system for content-based video retrieval using behavior, actions, and appearance with interactive query refinement," in IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS), Karlsruhe, Germany, 2015.
  5. K. Fieldhouse et al., "KWIVER: An open source cross-platform video exploitation framework," in Applied Imagery Pattern Recognition Workshop (AIPR), Washington, DC, USA, 2014.
  6. A. Basharat et al., "Real-time multi-target tracking at 210 megapixels/second in Wide Area Motion Imagery," in IEEE Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs, CO, USA, 2014.