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Face Detection And Recognition For Distributed Systems

Face Detection And Recognition For Distributed Systems. Meng Lin and Ermin Hod žić. Motivation. Security systems Digital cameras, adjustments Social networks Marketing. Fac e Detection. Locating and extracting faces in images Rectangles as output. Face Recognition.

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Face Detection And Recognition For Distributed Systems

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  1. Face Detection And Recognition ForDistributed Systems Meng Lin and ErminHodžić

  2. Motivation • Security systems • Digital cameras, adjustments • Social networks • Marketing

  3. Face Detection • Locating and extracting faces in images • Rectangles as output

  4. Face Recognition • Identifying person on image • Finding closest match

  5. MapReduce model • Parallel model • Framework for distributed systems • Hadoop local filesystem • Amazon Elastic MapReduce

  6. Solution: Face Detection

  7. Solution: Face Detection

  8. Solution: Face Detection • Partitions based on face scale

  9. Solution: Face Recognition • Distribution of recognizers • Recognizing in parallel • Reduce the most confident result

  10. Solution: Face Recognition

  11. Hadoop Image Handling • Images as text • Collection of images in a big file • Utilize Hadoop default input format

  12. Hadoop Image Handling

  13. Evaluation • Segmented Face Detection • Raw OpenCV Face Detection

  14. Evaluation • Face recognition • More nodes = slower • Input and data transfer overhead • Jobs computationally cheap

  15. Conclusion • Easily scalable parallel mode • Generalized framework • OpenCV just one sample tool • A lot of communication • Low utilization of processors

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