Augmented Reality
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Contents
Augmented Reality
With focus on facial recognition and social networking
cdpatel1 [1]
evmarbella [2]
evmarbella & cdpatel1 Email Group
Thesis Statement
Thesis
To what extent has HCI in facial recognition improved in a social network driven society.
Keywords
- Augmented Reality
- Mobile image search
- Mobile devices and productivity
- Face Recognition
- Social Networks
- Camera
- Tagging
- Ubiquity
- Multimodal Biometrics
- Cameraphone photos and sharing
Bibliography
http://library.senecacollege.ca/Find_Articles/
http://library.senecacollege.ca/resources/ebsco_asp.html
Primary
Choi, Kwontaeg, Kar-Ann Toh, and Hyeran Byun. "Realtime training on mobile devices for face recognition applications." Pattern Recognition 44.2 (2011): 386-400. Academic Search Premier. EBSCO. Web. 27 Oct. 2010. http://bit.ly/ceVBRT
ROKITA, JOANNA, ADAM KRZYŻAK, and CHING Y. SUEN. "MULTIMODAL BIOMETRICS BY FACE AND HAND IMAGES TAKEN BY A CELL PHONE CAMERA." International Journal of Pattern Recognition & Artificial Intelligence 22.3 (2008): 411-429. Academic Search Premier. EBSCO. Web. 27 Oct. 2010. http://bit.ly/dzSsbz
Van House, N., Davis, M., Ames, M., Finn, M., and Viswanathan, V. 2005. The uses of personal networked digital imaging: an empirical study of cameraphone photos and sharing. In CHI '05 Extended Abstracts on Human Factors in Computing Systems (Portland, OR, USA, April 02 - 07, 2005). CHI '05. ACM, New York, NY, 1853-1856. DOI= http://doi.acm.org/10.1145/1056808.1057039
Mavridis, N., Kazmi, W., Toulis, P., and Ben-Abdelkader, C. 2009. On the Synergies between Online Social Networking, Face Recognition and Interactive Robotics. In Proceedings of the 2009 international Conference on Computational Aspects of Social Networks (June 24 - 27, 2009). CASON. IEEE Computer Society, Washington, DC, 48-56. DOI= http://dx.doi.org/10.1109/CASoN.2009.28 http://www.irml.uaeu.ac.ae/irml/images/Publications/mavkaz_cason2009.pdf
NOV, ODED, and YE CHEN. "Why Do People Tag? Motivations for Photo Tagging." Communications of the ACM 53.7 (2010): 128-131. Academic Search Premier. EBSCO. Web. 1 Nov. 2010. http://web.ebscohost.com/ehost/detail?vid=1&hid=108&sid=abe7b0c2-e47b-4a82-82aa-d35152353d38%40sessionmgr111&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#db=aph&AN=8558868
Secondary
Menglei Jia, Xin Fan, Xing Xie, Mingjing Li, and Wei-Ying Ma. 2006. Photo-to- Search: Using Camera Phones to Inquire of the Surrounding World. In Proceedings of the 7th International Conference on Mobile Data Management (MDM '06). IEEE Computer Society, Washington, DC, USA, 46-. DOI=10.1109/MDM.2006.122 http://dx.doi.org/10.1109/MDM.2006.122
Reilly, R. B. 1998. Applications of face and gesture recognition for human-computer interaction. In Proceedings of the Sixth ACM international Conference on Multimedia: Face/Gesture Recognition and their Applications (Bristol, United Kingdom). MULTIMEDIA '98. ACM, New York, NY, 20-27. DOI= http://doi.acm.org/10.1145/306668.306677
Kong, S. G., Heo, J., Abidi, B. R., Paik, J., and Abidi, M. A. 2005. Recent advances in visual and infrared face recognition: a review. Comput. Vis. Image Underst. 97, 1 (Jan. 2005), 103-135. DOI= http://dx.doi.org/10.1016/j.cviu.2004.04.001
Ames, M. and Naaman, M. 2007. Why we tag: motivations for annotation in mobile and online media. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (San Jose, California, USA, April 28 - May 03, 2007). CHI '07. ACM, New York, NY, 971-980. DOI= http://doi.acm.org/10.1145/1240624.1240772
Choi, J. Y., De Neve, W., Ro, Y. M., and Plataniotis, K. N. 2009. Face annotation for personal photos using collaborative face recognition in online social networks. In Proceedings of the 16th international Conference on Digital Signal Processing (Santorini, Greece, July 05 - 07, 2009). IEEE Press, Piscataway, NJ, 240-247.
Tertiary
Pranav Mistry - Sixth Sense Project http://www.wired.com/epicenter/2009/02/ted-digital-six/f http://www.pranavmistry.com/projects/sixthsense/
John Maeda - The Laws of Simplicity http://lawsofsimplicity.com/ (Web)
Face detection and gesture recognition for human-computer interaction By Ming-Hsuan Yang, Narendra Ahuja (google books)[ http://books.google.com/books?id=zS0AZgdAJBsC&lpg=PP1&ots=iwY1ShiMHM&dq=first%20hand%20research%20in%20face%20recognition&pg=PP1#v=onepage&q=first%20hand%20research%20in%20face%20recognition&f=false]
Face Detection and Gesture Recognition for Human-Computer Interaction (ACM)[ http://portal.acm.org/citation.cfm?id=558181&coll=Portal&dl=GUIDE&CFID=109120439&CFTOKEN=76327335]
A camera-based mobile data channel: capacity and analysis (ACM)[ http://portal.acm.org/citation.cfm?id=1220973.1221344&coll=Portal&dl=GUIDE&CFID=109120439&CFTOKEN=76327335]
Wikipedia - Face Detection (Wikipedia)[ http://en.wikipedia.org/wiki/Face_detection]
Research Notes
Introduction & Definition of Face Recognition Technology
http://en.wikipedia.org/wiki/Facial_recognition_system#Early_development
How does the technology work (overview)?
Effectiveness of Point Distribution Model and Active Shape Models:
“The point distribution model can be used for Face detection and face recognition.”
ROKITA, JOANNA, ADAM KRZYŻAK, and CHING Y. SUEN. "MULTIMODAL BIOMETRICS BY FACE AND HAND IMAGES TAKEN BY A CELL PHONE CAMERA." International Journal of Pattern Recognition & Artificial Intelligence 22.3 (2008): 411-429. Academic Search Premier. EBSCO. Web. 1 Nov. 2010.
Uses of the technology.
Facial recognition for personal security:
“ face detection methods can be categorized into the following two large groups:
1) heuristic-based methods and 2) classification-based methods.”
“The following two popular ways of doing the face registration can be found in the literature: 1) holistic
methods and 2) local methods.”
“Illumination normalization, therefore, is a very important preprocessing step before verification.”
Face Verification is math heavy This calculates thresholds (I think). We will worry about that later. Even Chris would love to explain this heavy math, if we need his help.
Information Fusion
“From each frame, we obtain a value of its likelihood ratio and compare it to a threshold to make the decision”
Facial recognition for fighting terrorism:
“A technique such as face recognition could, at least in principle, be used to recognize people
“passively,” without their knowledge or cooperation.”
“Instead of a person continuously monitoring the video, the goal is to have a computer monitor the
video and alert a human operator if an “interesting person” is in view.”
System Dependencies: “the system can only recognize the persons whose images have been enrolled in the gallery”
“If a terrorist is known by name and reputation, but no picture of the terrorist is available, then the face
recognition system is useless.”
“system must be able to acquire face images of reasonable quality to use as probes.”
“system has a sensitivity threshold that must be set appropriately.”
Bowyer, Kevin W. "Face Recognition Technology: Security versus Privacy." IEEE Technology & Society Magazine 23.1 (2004): 9-20. Academic Search Premier. EBSCO. Web. 1 Nov. 2010.
Facial recognition for search realistically.
“Imagine never forgetting a face, and always being able to recognize a friend-of-a-friend on the street. And because the systems arelinked to the Internet, once AR recognized someone, you could easily pull up his or her online footprint, such as a Facebook page.”
Cascio, Jamais. "Seeing Too Much." Atlantic Monthly (10727825) 304.4 (2009): 34. Academic Search Premier. EBSCO. Web. 1 Nov. 2010.
Problems due to technology.
Facial recognition vs. privacy in social media driven world:
1. “The United States Constitution declares a level of protection for the rights of individual citizens
against oppression by their government that has made the U.S. unique. The right to privacy is one right that has become a firmly entrenched American value, even though it is not explicitly enumerated in the Constitution. Since face recognition systems represent leading-edge and rapidly changing technology, this technology is currently a major issue in the area of social impact of technology.”
Bowyer, Kevin W. "Face Recognition Technology: Security versus Privacy." IEEE Technology & Society Magazine 23.1 (2004): 9-20. Academic Search Premier. EBSCO. Web. 1 Nov. 2010.
2. 2. “We don’t regard ourselves as ‘Big Brother’. We’re more like a friendly uncle or aunt
watching over you.”
Hale, Benjamin. "Identity crisis: Face recognition technology and freedom of the will." Ethics, Place & Environment 8.2 (2005): 141-158. Academic Search Premier. EBSCO. Web. 1 Nov. 2010.
Facial recognition false positives.
“Distinctiveness of a face predicts both miss errors (MEs) and false positives (FPs) but correlations
between these errors are low”
Lewis, Michael B. "Familiarity, Target Set and False Positives in Face Recognition." European Journal of Cognitive Psychology 9.4 (1997): 437-459. Academic Search Premier. EBSCO. Web. 1 Nov. 2010.
