Post on 29-Dec-2015
Face Detection And Recognition ForDistributed SystemsMeng Lin and Ermin Hodžić
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Motivation
• Security systems•Digital cameras, adjustments• Social networks•Marketing
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Face Detection
• Locating and extracting faces in images•Rectangles as output
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Face Recognition
• Identifying person on image• Finding closest match
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MapReduce model
•Parallel model• Framework for distributed systems•Hadoop local filesystem•Amazon Elastic MapReduce
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Solution: Face Detection
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Solution: Face Detection
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Solution: Face Detection
•Partitions based on face scale
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Solution: Face Recognition
•Distribution of recognizers•Recognizing in parallel•Reduce the most confident result
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Solution: Face Recognition
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Hadoop Image Handling
• Images as text•Collection of images in a big file•Utilize Hadoop default input format
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Hadoop Image Handling
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Evaluation
• Segmented Face Detection
•Raw OpenCV Face Detection
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Evaluation
• Face recognition
•More nodes = slower• Input and data transfer overhead• Jobs computationally cheap
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Conclusion
• Easily scalable parallel mode•Generalized framework• OpenCV just one sample tool
•A lot of communication• Low utilization of processors
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