IEEE Consumer Electronics Magazine - May 2018 - 31

food images in a stable manner, with a reasonable food identification rate.

ABOUT THE AUTHORS
Haotian Jiang (hxj172@case.edu) is with the Department of
Electrical and Computer Science, Case Western Reserve University, Cleveland, Ohio.
James Starkman (jas497@case.edu) is with the Department of Electrical and Computer Science, Case Western
Reserve University, Cleveland, Ohio.
Menghan Liu (mxl677@case.edu) is with the Department
of Electrical and Computer Science, Case Western Reserve
University, Cleveland, Ohio.
Ming-Chun Huang (mxh602@case.edu) is with the
Department of Electrical and Computer Science, Case Western Reserve University, Cleveland, Ohio.

REFERENCES
[1] Most common English words. [Online]. Available: http://ucrel.lancs
.ac.uk/bncfreq/lists/1_2_all_freq.txt
[2] National Nutrient Database. (2015). Welcome to the USDA food
composition databases. U.S. Dept. Agriculture, Washington, D.C.
[Online]. Available: https://ndb.nal.usda.gov/
[3] J. Ahn, J. Williamson, M. Gartrell, R. Han, Q. Lv, and S. Mishra,
"Supporting healthy grocery shopping via mobile augmented reality,"
ACM Trans. Multimed. Comput., Commun., Applicat., vol. 12, no. 1s,
pp. 16, 2015. doi: 10.1145/2808207.
[4] J. Barreiro-Hurlé, A. Gracia, and T. De-Magistris, "Does nutrition
information on food products lead to healthier food choices?" Food Policy, vol. 35, no. 3, pp. 221-229, 2010.
[5] S. Burton, E. H. Creyer, J. Kees, and K. Huggins, "Attacking the obesity epidemic: The potential health benefits of providing nutrition
information in restaurants," Amer. J. Public Health, vol. 96, no. 9,
pp. 1669-1675, 2006.
[6] M. Calonder, V. Lepetit, C. Strecha, and P. Fua, "BRIEF: Binary
Robust Independent Elementary Features," in Proc. European Conf.
Computer Vision (ECCV), 2010, pp. 778-792.
[7] J. S. Downs, G. Loewenstein, and J. Wisdom, "Strategies for promoting healthier food choices," Amer. Econ. Rev., vol. 99, no. 2, pp. 159-
164, 2009.
[8] R. H. Eckel, Obesity: Mechanisms and Clinical Management. Philadelphia: Lippincott Williams & Wilkins, 2003.
[9] H. Kalantarian, N. Alshurafa, and M. Sarrafzadeh, "A wearable nutrition monitoring system," in Proc. IEEE 11th Int. Conf. Wearable and
Implantable Body Sensor Networks, 2014, pp. 75-80.
[10] Y. Kawano and K. Yanai, "Real-time mobile food recognition system," in Proc. IEEE Conf. Computer Vision and Pattern Recognition
Workshops, 2013, pp. 1-7.
[11] R. LiKamWa, Z. Wang, A. Carroll, F. X. Lin, and L. Zhong, "Draining our glass: An energy and heat characterization of Google Glass," in
Proc. ACM 5th Asia-Pacific Workshop Systems, 2014. doi: 10.1145/
2637166.2637230.
[12] J. Liu, E. Johns, L. Atallah, C. Pettitt, B. Lo, G. Frost, and G.-Z.
Yang, "An intelligent food-intake monitoring system using wearable sensors," in Proc. IEEE 9th Int. Conf. Wearable and Implantable Body Sensor Networks, 2012, pp. 154-160.
[13] K. Ofei, M. Dobroczynski, M. Holst, H. Rasmussen, and B.
Mikkelsen, "The Dietary Intake Monitoring System (DIMS): An
innovative device for capturing patients' food choice, food intake
and plate waste in a hospital setting," in Proc. Measuring Behavior,
2014, pp. 27-29.

[14] C. L. Ogden, M. D. Carroll, B. K. Kit, and K. M. Flegal, "Prevalence of childhood and adult obesity in the United States, 2011-2012," J.
Amer. Med. Assn., vol. 311, no. 8, pp. 806-814, 2014.
[15] S. Passler and W.-J. Fischer, "Acoustical method for objective
food intake monitoring using a wearable sensor system," in Proc. IEEE
5th Int. Conf. Pervasive Computing Technologies Healthcare, 2011,
pp. 266-269.
[16] M. Puri, Z. Zhu, Q. Yu, A. Divakaran, and H. Sawhney, "Recognition and volume estimation of food intake using a mobile device," in
Proc. Workshop Applications Computer Vision, 2009, pp. 1-8.
[17] D. Roberts, A. Menozzi, J. Cook, T. Sherrill, S. Snarski, P. Russler,
B. Clipp, R. Karl, E. Wenger, M. Bennett, and J. Mauger, "Testing and
evaluation of a wearable augmented reality system for natural outdoor
environments," in Proc. 18th Head- and Helmet-Mounted Displays:
Design and Applications, vol. 8735, 2013. doi: 10.1117/12.2015621.
[18] S. A. Rogers, "Preparation and use of food-based dietary guidelines," J. Nutritional Environ. Med., vol. 10, no. 2, pp. 167, 2000.
[19] P. L. Rosin, "Measuring corner properties," Comput. Vision Image
Understand., vol. 73, no. 2, pp. 291-307, 1999.
[20] E. Rosten and T. Drummond, "Machine learning for high-speed
corner detection," in Proc. European Conf. Computer Vision, 2006,
pp. 430-443.
[21] E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, "ORB: An efficient alternative to SIFT or SURF," in Proc. IEEE Int. Conf. Computer
Vision, 2011, pp. 2564-2571.
[22] M. Sharif, S. Mohsin, M. J. Jamal, and M. Raza, "Illumination normalization preprocessing for face recognition," in Proc. 2nd Conf. Environmental Science and Information Application Technology, 2010,
pp. 44-47.
[23] G. Shroff, A. Smailagic, and D. P. Siewiorek, "Wearable contextaware food recognition for calorie monitoring," in Proc. 12th IEEE Int.
Symp. Wearable Computers, 2008, pp. 119-120.
[24] Mayo Clinic. (2018). Obesity. [Online]. Available: http://www
.mayoclinic.org/diseases-conditions/obesity/basics/definition/con20014834
[25] T. Stutz, R. Dinic, M. Domhardt, and S. Ginzinger. "Can mobile
augmented reality systems assist in portion estimation? A user study," in
Proc. IEEE Int. Symp. Mixed and Augmented Reality: Media, Art, Social
Science, Humanities and Design, 2014, pp. 51-57.
[26] Š. Marko, "Automatic fruit recognition using computer vision,"
B.Sc. thesis, Mentor: Matej Kristan, Fakulteta za racˇunalništvo in informatiko, Univerza v Ljubljani, 2013.
[27] G. Waltner, M. Schwarz, S. Ladstätter, A. Weber, P. Luley, H.
Bischof, M. Lindschinger, I. Schmid, and L. Paletta, "MANGO: Mobile
augmented reality with functional eating guidance and food awareness,"
in Proc. Int. Conf. Image Analysis and Processing Workshops (New
Trends in Image Analysis and Processing), Springer, 2015, pp. 425-432.
[28] J. Wardle, K. Parmenter, and J. Waller, "Nutrition knowledge and
food intake," Appetite, vol. 34, no. 3, pp. 269-275, 2000.
[29] J. Wei, "How wearables intersect with the cloud and the Internet of
Things: Considerations for the developers of wearables," IEEE Consum.
Electron. Mag., vol. 3, no. 3, pp. 53-56, 2014.
[30] World Health Organization. (2017, Oct.). Obesity and overweight.
[Online]. Available: http://www.who.int/mediacentre/factsheets/fs311/en/
[31] Z. Wu, Q. Ke, M. Isard, and J. Sun, "Bundling features for large
scale partial-duplicate web image search," in Proc. IEEE Conf. Computer
Vision and Pattern Recognition, 2009, pp. 25-32.
[32] X. Yang and K.-T. Cheng, "Learning optimized local difference
binaries for scalable augmented reality on mobile devices," IEEE Trans.
Vis. Comput. Graphics, vol. 20, no. 6, pp. 852-865, 2014.
[33] X. Yang and K.-T. Cheng, "Local difference binary for ultrafast and
distinctive feature description," IEEE Trans. Pattern Anal. Mach. Intell.,
vol. 36, no. 1, pp. 188-194, 2014.

MAy 2018

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http://ucrel.lancs.ac.uk/bncfreq/lists/1_2_all_freq.txt http://ucrel.lancs.ac.uk/bncfreq/lists/1_2_all_freq.txt https://ndb.nal.usda.gov/ http://www.mayoclinic.org/diseases-conditions/obesity/basics/definition/con-20014834 http://www.mayoclinic.org/diseases-conditions/obesity/basics/definition/con-20014834 http://www.who.int/mediacentre/factsheets/fs311/en/
Table of Contents for the Digital Edition of IEEE Consumer Electronics Magazine - May 2018
