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Proceedings ArticleDOI
Yuting Ng, Grace Xingxin Gao 
11 Apr 2016
13 Citations
In this manner, the entire received signal information is utilized, leading to increased robustness in tracking.
The results show that the tracking system is capable of target shape recovery and therefore it can successfully track targets with varying distance from camera or while the camera is zooming.
We first show that received signal strength indicator and link quality indicator are not as effective as expected for passive detection (tracking) through our extensive testbed studies, and further propose to utilize light to track targets using WSNs.
This automatic identification of the visual context required for tracking allows the proposed method to potentially track any point on the face.
These data from screenshots have the potential to provide key insights into precise mobile smartphone screen use and time spent per mobile app.
The results show effective tracking performance using this approach, yielding a single high quality target track with zero false tracks.
Our evaluation shows that the tracking system correctly detects each track over 98% of the time.
The accuracy of the signal acquisition has a direct influence on the tracking performance.
Movement tracking during imaging may allow for prospective correction or postprocessing steps separating signal and noise.