IEEE Consumer Electronics Magazine - May 2018 - 80

detection region would greatly improve the user's experience. In addition, HoloLens recognizes only limited gestures for now, so more gestures need to be defined to
facilitate the interaction experience.

CONCLUSION
This article discussed the method of visualizing Toronto city
data with the cutting-edge AR device HoloLens. The city
model and data sets are shown as augmented contents in the
real world through the lenses. With our implementation, the
user can achieve an interactive view of the Toronto city data
and obtain the information of a selected city data object in
detail. We also discussed the comparison among AR, VR, and
traditional monitor use, explored the computing power of
HoloLens, and proposed improvements for gesture detection.
Currently, we consider only the visualization of the city
data point objects generated through data files, and we directly display them above the city model. A future extension may
contain a real-time parallel-computing mechanism to stream
up-to-date data from databases, visualizing more data object
types (such as polylines and polygons), displaying multiple
city data layers at the same time in a smart way, and showing
the patterns of city data in more depth.

ABOUT THE AUTHORS
Longyu Zhang (lzhan121@uottawa.ca) earned his B.Eng.
degree in telecommunications engineering from Tianjin Polytechnic University, China, in 2010 and his M.A.Sc. degree in
electrical and computer engineering from the University of Ottawa, Canada, in 2012. He is currently pursuing his Ph.D. degree
in electrical and computer engineering at the Multimedia Computing Research Laboratory, University of Ottawa. He has been
awarded the National Sciences and Engineering Research Council of Canada Postgraduate Scholarship (Doctoral) for the years
2015-2018. His research interests include augmented reality,
multimedia applications, and haptics.
Sifeng Chen (schen204@uottawa.ca) earned his master's
degree in computer science from the University of Ottawa,
Canada, in 2016. His research interests include computer
vision and cloud computing.
Haiwei Dong (hdong@uottawa.ca) earned his M.Eng.
degree in control theory and control engineering from Shanghai Jiao Tong University, China, in 2008 and his Ph.D. degree
in computer science and systems engineering from Kobe University, Japan, in 2010. He is a research scientist at the
School of Electrical Engineering and Computer Science at
the University of Ottawa, Canada; a senior research engineer
at Huawei Canada Research Center, Kanata; and a licensed
professional engineer in Canada. His research interests
include robotics, multimedia, haptics, and control. He is a
Senior Member of the IEEE.
Abdulmotaleb El Saddik (elsaddik@uottawa.ca) earned
his Dipl.-Ing. and Dr.-Ing. degrees in electrical engineering
from Darmstadt University of Technology, Germany, in 1995
and 2001, respectively. He is a distinguished university professor at the University of Ottawa, Canada. His research
80 IEEE Consumer Electronics Magazine

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focus is on multimodal interactions with sensory information
in smart cities. He received the IEEE Instrumentation and
Measurement Society Technical Achievement Award and the
IEEE Canada Computer Medal. He is an Association for
Computing Machinery Distinguished Scientist, a fellow of
the Engineering Institute of Canada, and a fellow of the
Canadian Academy of Engineers. He is a Fellow of the IEEE.

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