1. Face Detection And Recognition For Distributed Systems Meng Lin and Ermin Hodžić 1

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

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

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

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

6. Solution: Face Detection 6

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8. Partitions based on face scale 8

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

10. Solution: Face Recognition 10

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

12. Hadoop Image Handling 12

13. Evaluation Segmented Face Detection Raw OpenCV Face Detection 13

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

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

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