TY - GEN
T1 - Robust and reliable step counting by mobile phone cameras
AU - Ozcan, Koray
AU - Velipasalar, Senem
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/9/8
Y1 - 2015/9/8
N2 - Wearable sensors are being widely used to monitor daily human activities and vital signs. Accelerometer-based step counters are commonly available, especially after being integrated into smart- phones and smart watches. Moreover, accelerometer data is also used to measure step length and frequency for indoor positioning systems. Yet, accelerometer-based algorithms are prone to over- counting, since they also count other routine movements, including movements of the phone, as steps. In addition, when users walk really slowly, or when they stop and start walking again, the accelerometer-based counting becomes unreliable. Since accurate step detection is very important for indoor positioning systems, more precise alternatives are needed for step detection and counting. In this paper, we present a robust and reliable method for counting foot steps using videos captured with a Samsung Galaxy® S4 smartphone. The performance of the proposed method is com- pared with existing accelerometer-based step counters. Experiments have been performed with different subjects carrying five mobile devices simultaneously, including smart phones and watches, at different locations on their body. The results show that camera-based step counting has the lowest average error rate for different users, and is more reliable compared to accelerometer-based counters. In addition, the results show the high sensitivity of the accelerometer- based step counters to the location of the device and high variance in their performance across different users.
AB - Wearable sensors are being widely used to monitor daily human activities and vital signs. Accelerometer-based step counters are commonly available, especially after being integrated into smart- phones and smart watches. Moreover, accelerometer data is also used to measure step length and frequency for indoor positioning systems. Yet, accelerometer-based algorithms are prone to over- counting, since they also count other routine movements, including movements of the phone, as steps. In addition, when users walk really slowly, or when they stop and start walking again, the accelerometer-based counting becomes unreliable. Since accurate step detection is very important for indoor positioning systems, more precise alternatives are needed for step detection and counting. In this paper, we present a robust and reliable method for counting foot steps using videos captured with a Samsung Galaxy® S4 smartphone. The performance of the proposed method is com- pared with existing accelerometer-based step counters. Experiments have been performed with different subjects carrying five mobile devices simultaneously, including smart phones and watches, at different locations on their body. The results show that camera-based step counting has the lowest average error rate for different users, and is more reliable compared to accelerometer-based counters. In addition, the results show the high sensitivity of the accelerometer- based step counters to the location of the device and high variance in their performance across different users.
KW - Camera
KW - Indoor positioning
KW - Smartphone
KW - Step counter
KW - Vision-based
UR - http://www.scopus.com/inward/record.url?scp=84958259129&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84958259129&partnerID=8YFLogxK
U2 - 10.1145/2789116.2789120
DO - 10.1145/2789116.2789120
M3 - Conference contribution
AN - SCOPUS:84958259129
T3 - ACM International Conference Proceeding Series
SP - 164
EP - 169
BT - 9th International Conference on Distributed Smart Cameras, ICDSC 2015
PB - Association for Computing Machinery
T2 - 9th International Conference on Distributed Smart Cameras, ICDSC 2015
Y2 - 8 September 2015 through 11 September 2015
ER -