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Design and Implement a Face Tracking Engine for Video

Design and Implement a Face Tracking Engine for Video. Undertaken By: William O’ Grady Project Supervisor and Co Supervisor Dr. Peter Corcoran and Dr. John Breslin. What is Face Detection. A targeted area of object class detection.

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Design and Implement a Face Tracking Engine for Video

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  1. Design and Implement a Face Tracking Engine for Video Undertaken By: William O’ Grady Project Supervisor and Co Supervisor Dr. Peter Corcoran and Dr. John Breslin

  2. What is Face Detection • A targeted area of object class detection. • Object class detection is used daily, such as pedestrian detection in smart traffic lights. • Face detection thus has many applications: • Auto focus for cameras • Security systems • Smart marketing or advertising billboards

  3. Basic Objectives • Research various techniques of face detection on real time video feed • Review most renowned algorithm (Viola - Jones Algorithm) • Design and implement basic algorithm for face detection on real time video feed

  4. Advanced Objectives • Research into improvements in FPS through image pre-processing and face tracking techniques • Implement these techniques and improve on the basic algorithm. • Implement design on embedded device (Android Application) • Develop an evaluation methodology • Produce algorithm which allows real-time tracking at 25+ frame rates or HD video steams (>720p)

  5. Progress to Date • Researched different techniques for face detection • Reviewed current “state-of-art” face detection algorithm • Develop a working algorithm • Tested on live webcam feed • Developed a tracking algorithm for single-frame face detection • Researched into improving algorithm through further pre-processing and/or using multiple images to provide an effective tracking system • Researched various methods for Android implementation

  6. Website • All up to date weekly progress, documents and relevant information can be found here: • http://williamogradyfyp.wordpress.com/

  7. Demonstration • Webcam • Video Feed

  8. Objectives Remaining • Evaluate research of object tracking through pattern matching and/or pre-filtering • Implement design on an embedded device (Android Application) • An evaluation methodology needs to be developed • Develop algorithm which provides real-time tracking at 25+ FPS or on HD video streams (720p or higher) • Develop final design and test on a real-time video feed.

  9. Development Plan

  10. Thanks for your time! • I would be happy to answer any questions that you may have

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