Panacea
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it's an Augmented reality android app which can be used inside an enterprise to manage contacts and location services
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Panacea
- 2. Tracking-Learning-Detection (Predator ) Algorithm HCI Demo using Virtual Mouse
- 3. Augmented Reality? Overlaying of digital data on the real world
- 4. The Team Navneet Nikhil Manohar Ritesh http://tinyurl.com/twdemo
- 5. We built “ An augmented reality application to be used inside an Enterprise to manage contacts and location services. “
- 6. PANACEA TWANACEA * Possible names for the application
- 9. Contacts Problems Not Updated Unmanageable Non-scalable
- 10. Contacts Problems Wait! Is there a name of a person as well? So, now I know the person as well his/her phone number. What happens if the Phone number changes? Exposed Phone numbers
- 11. Contacts Problems Navneet KumarDeveloper ThoughtWorks Technologies (India) Pvt Ltd2nd Floor, Tower C, Corporate Block, Diamond District Airport Road, Bangalore - 560 008, Indiatel : +91 80 4064 9570, fax : +91 9686577076 navneetk@thoughtworks.com … passé
- 12. Contacts Problems Future of Visiting Cards Navneet Kumar With Best Wishes ThoughtWorks Technologies (India) Pvt Ltd2nd Floor, Tower C, Corporate Block, Diamond District Airport Road, Bangalore - 560 008, Indiatel : +91 80 4064 9570, fax : +91 9686577076 navneetk@thoughtworks.com . . .You know why?
- 13. Contacts Problems My only use for it now is to attach it to gifts that I give.
- 14. A radical new way of exchanging contacts inside the enterprise vCards 2.0
- 16. You meet these guys at Dev-Camp. How long do you think it will take you exchange your contact information? We say about 10 seconds!
- 17. Possibilities … * Stock photo from stck.xchng
- 18. A new way of putting up Assistance and event posters. Posters
- 19. A new way of putting up assistance posters. No numbers, no hassles. For all Travel related Queries Logon to PANACEA Powered by PANACEA
- 20. X-Conf 4 – March 5th Event Posters - Revisited //TODO: Add functionality that will add this event to your calendar and notify you 10 mins before the event Don't do that, then! (Doctor, it hurts when I rewrite legacy applications) Powered by PANACEA * Photo courtesy thoughtworker.com
- 21. Presence * VISION @starkcoffee - hopefully my.thoughtworks will be a completely fresh experience to TWers !
- 22. * VISION Dinesh Tantri – Geek Lunch Talk: Introducing myThoughtWorks Give Feedback , ask questions Logon to PANACEA Powered by PANACEA Event / Conference Feedback(1/2) PANACEA
- 23. Event / Conference Feedback(2/2) * VISION Talk: Introducing my.thoughtworks! Comments Feedback PANACEA
- 24. How we do this. Tech
- 25. Application Walkthrough
- 27. Step 1 Detecting… No Faces in this Image
- 28. Step 2 Scanning… A Face Found !!!
- 29. Step 3 Fetching… Fetch Data From Active Directory PratekhsaUday Prateeksha@thoughtworks.com Mobile : 9686577076
- 30. Implementation and Challenges Uh Oh!
- 31. First Approach Training Set Manual Training Face Detection LDAP Face Recognition Service Calls App Massive Database of Photos
- 32. Problems with this approach Too Painful Training Set Manual Training Face Detection Face Recognition Service Calls App Not Real time – Not scalable
- 33. Second Approach Gives Compile Using opencv.so C++ Libraries Android NDK opencv.so Java Native Interface (JNI) App
- 35. Pros & Cons - Second Approach opencv.so Java Native Interface (JNI) App Not Accurate Near Real time No Service Calls Poor Training data Totally in Phone
- 37. Hybrid Approach Face Detection Scanning Mode Face? Yes Face Recognition Training Mode
- 38. Train Every Employee ?? Damn ! It’s painful
- 41. Do you know these applications? * Logos courtesy their corresponding websites
- 42. Location Problems Only 13% of the smart phones sold across the world are Location Aware Less than 4% of all mobile phones sold last year were Location aware. * Stats courtesy: http://textopiablog.wordpress.com/2010/02/22/how-many-people-own-a-location-aware-device/
- 43. Location Problems Too many places. Search doesn’t solve the problem either. *screen shot courtesy google.com
- 44. Location Problems Roof top Restaurant Roof top - Bar Pizzeria Chinese Restaurant Cafe Multiple Avenues – Same GPS Location
- 45. Creating and using GPS agnostic Hyper local communities Location
- 46. Introducing the PlaceMark! Join my community and share your thoughts
- 48. Enterprise Network Chicago Bangalore Pune Chennai Melbourne
- 49. Implementation Face Detection Scanning Mode Face? Yes Face Recognition Location?
- 50. Application Architecture Main UI Surface Overlays Camera Info Overlay status Overlay Processing Android native detection Recognition service Gab server Location server PANACEA
Hinweis der Redaktion
- Augmented reality (AR) is a term for a live direct or an indirect view of a physical, real-world environment whose elements are augmented by computer-generated sensory input, such as sound or graphics. Simple Defn : overlaying of digital data on the real world.
- Face Recognition – Once a face is detected, the face has to be processed by an algorithm which will associate a unique id from the training set.
- Once the algorithm returns a unique identifier based on the processed image, we fetch the data corresponding to that id. In our case, the details from Active Directory. (actually, not just AD)
- We found Open Source Computer Vision. A free library that does object detection, recognition and 500 other image processing algorithm
- This video visualizes the detection process of OpenCV's face detector. The algorithm uses the Viola Jones method of calculating the integral image and then performing some calculations on all the areas defined by the black and white rectangles to analyze the differences between the dark and light regions of a face. The sub-window (in red) is scanned across the image at various scales to detect if there is a potential face within the window. If not, it continues scanning. If it passes all stages in the cascade file, it is marked with a red rectangle. But this does not yet confirm a face. In the post-processing stage all the potential faces are checked for overlaps. Typically, 2 or 3 overlapping rectangles are required to confirm a face. Loner rectangles are rejected as false-positives.In stead of finding faces, the algorithm should discard non-faces.