TY - GEN
T1 - I am a smartphone and I can tell my user's walking direction
AU - Roy, Nirupam
AU - Wang, He
AU - Roy Choudhury, Romit
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2014
Y1 - 2014
N2 - This paper describes WalkCompass, a system that exploits smartphone sensors to estimate the direction in which a user is walking. We find that several smartphone localization systems in the recent past, including our own, make a simplifying assumption that the user's walking direction is known. In trying to relax this assumption, we were not able to find a generic solution from past work. While intuition suggests that the walking direction should be detectable through the accelerometer, in reality this direction gets blended into various other motion patterns during the act of walking, including up and down bounce, side-to-side sway, swing of arms or legs, etc. Moreover, the walking direction is in the phone's local coordinate system (e.g., along Y axis), and translation to global directions, such as 45 degree North, can be challenging when the compass is itself erroneous. WalkCompass copes with these challenges and develops a stable technique to estimate the user's walking direction within a few steps. Results drawn from 15 different environments demonstrate median error of less than 8 degrees, across 6 different users, 3 surfaces, and 3 holding positions. While there is room for improvement, we believe our current system can be immediately useful to various applications centered around localization and human activity recognition.
AB - This paper describes WalkCompass, a system that exploits smartphone sensors to estimate the direction in which a user is walking. We find that several smartphone localization systems in the recent past, including our own, make a simplifying assumption that the user's walking direction is known. In trying to relax this assumption, we were not able to find a generic solution from past work. While intuition suggests that the walking direction should be detectable through the accelerometer, in reality this direction gets blended into various other motion patterns during the act of walking, including up and down bounce, side-to-side sway, swing of arms or legs, etc. Moreover, the walking direction is in the phone's local coordinate system (e.g., along Y axis), and translation to global directions, such as 45 degree North, can be challenging when the compass is itself erroneous. WalkCompass copes with these challenges and develops a stable technique to estimate the user's walking direction within a few steps. Results drawn from 15 different environments demonstrate median error of less than 8 degrees, across 6 different users, 3 surfaces, and 3 holding positions. While there is room for improvement, we believe our current system can be immediately useful to various applications centered around localization and human activity recognition.
KW - activity recognition
KW - compass correction
KW - force analysis
KW - heading direction
KW - localization
KW - magnetic field
KW - mobile phones
KW - orientation
KW - sensing
UR - http://www.scopus.com/inward/record.url?scp=84903132202&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84903132202&partnerID=8YFLogxK
U2 - 10.1145/2594368.2594392
DO - 10.1145/2594368.2594392
M3 - Conference contribution
AN - SCOPUS:84903132202
SN - 9781450327930
T3 - MobiSys 2014 - Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services
SP - 329
EP - 342
BT - MobiSys 2014 - Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services
PB - Association for Computing Machinery
T2 - 12th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2014
Y2 - 16 June 2014 through 19 June 2014
ER -