VisageCloud - Face Recognition meets Big Data
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VisageCloud merges state-of-the-art deep learning algorithms for face recognition and classification with data querying, tagging and querying techniques so as to empower you to leverage the full value of your data. Face recognition meets big data. In cloud or on-premise.
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VisageCloud - Face Recognition meets Big Data
- 2. Agenda Context Use Cases Demo: what actors you look like? Features Face Detection Classification Feature Extraction & Analysis Competition Analysis Roadmap Technical Performance Offering
- 3. The Context Market size estimated* to reach 6.8 – 9.6 billion USD worldwide by 2022 Machine face recognition comparable to human capabilities Computational effort required for analysis economically feasible Face analysis has attracted big players from the industry (Amazon, Microsoft)
- 4. Use Cases Online dating: finding members who are attractive or similar to reference photo In-door advertisement targeting In-store and omni-channel identification of returning customers Media and usability usability Sorting photo albums Security Smart surveillance Home surveillance Law enforcement National Biometric Identification System Border control
- 5. Demo: What actors you look like? Try it on http://visagecloud.com
- 6. Features • Find position • Get face keypoints • Determine orientation Face Detection • Gender • Age • Mood • Hair/Eye/Skin Color Classification • Encode face signature • Compare to known persons • Store and tag signature Feature Extraction & Analysis
- 7. Face Detection Location. Key points. Spatial orientation.
- 11. Classification Gender. Age. Skin/eye/hair color. Mood.
- 13. Feature Extraction & Analysis Demo: Who’s the actor? Who’s your celebrity lookalike?
- 16. Peter Jackson Fergal Devitt Robert Swanson
- 17. Technical Performance Detection, analysis on a 1MP photo and comparison against 5000 reference profiles (actors) Time: 2.3-2.5 seconds on one core Throughput/core/hour: >1000 pictures (assuming 1MP average size) Scalable, distributed architecture Executes on several multi-core machines Highly available data store with replication (Cassandra)
- 18. Offering SaaS Cloud Billed monthly Based on consumption On-Premise Up-front fee Monthly support fee Consulting Integration Custom Requirements On-demand
Notas do Editor
- * http://www.marketsandmarkets.com/PressReleases/facial-recognition.asp * http://www.prnewswire.com/news-releases/facial-recognition-market-is-expected-to-reach-96-billion-worldwide-by-2022-584841741.html