Android smartphone usage as a pedestrian tracking system

2016 ◽  
Author(s):  
Yasmine Fahmy
Keyword(s):  
Tracking System ◽  
Pedestrian Tracking

A Modified Multi-Pedestrian Tracking System

2019 ◽  
Author(s):  
Yuan Gong ◽  
Jianning Chi ◽  
Xiaosheng Yu ◽  
Chengdong Wu ◽  
Zixi Jia
Keyword(s):  
Tracking System ◽  
Pedestrian Tracking

Economic and Synergistic Pedestrian Tracking System with Service Cooperation for Indoor Environments

2011 ◽  
Vol 2 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Tomoya Ishikawa ◽  
Masakatsu Kourogi ◽  
Takeshi Kurata
Keyword(s):  
Indoor Environment ◽  
Tracking System ◽  
Tracking Performance ◽  
Quality Of Services ◽  
Rfid Tags ◽  
Indoor Environments ◽  
Pedestrian Tracking ◽  
Security Services ◽  
Indoor Pedestrian Tracking

This paper describes an indoor pedestrian tracking system that can economically improve the tracking performance and the quality and value of services by incorporating other services synergistically. The tracking system obtains position, orientation, and action of pedestrians continuously and accurately in large indoor environments by utilizing surveillance cameras and active RFID tags for security services and 3-D environment models for navigation services. Considering service cooperation and co-creative intelligence cycles, this system can improve both the tracking performance and the quality of services without significant increase of costs by sharing the existing infrastructures and the 3-D models among services. The authors conducted an evaluation of the tracking system in a large indoor environment and confirmed that the accuracy of the system can be improved by utilizing the infrastructures and the 3-D models. Synergistic services utilizing the tracking system and service cooperation can also enhance the quality and value of services.

scholarly journals Smartphone-Based Indoor Pedestrian Tracking Using Geo-Magnetic Observations

2013 ◽  
Vol 9 (2) ◽  
pp. 123-137 ◽  
Author(s):  
Sungnam Lee ◽  
Yohan Chon ◽  
Hojung Cha
Keyword(s):  
Environmental Changes ◽  
Tracking System ◽  
Magnetic Sensors ◽  
Location Based Services ◽  
Location Tracking ◽  
Magnetic Fluctuations ◽  
Pedestrian Tracking ◽  
Estimation Model ◽  
Indoor Location ◽  
Extensive Evaluation

With the widespread use of smartphones, the use of location-based services (LBS) with smartphones has become an active research issue. The accurate measurement of user location is necessary to provide LBS. While outdoor locations are easily obtained with GPS, indoor location information is difficult to acquire. Previous work on indoor location tracking systems often relied on infrastructures that are influenced by environmental changes and temporal differences. Several studies have proposed infrastructure-less systems that are independent of the surroundings, but these works generally required non-trivial computation time or energy costs. In this paper, we propose an infrastructure-less pedestrian tracking system in indoor environments. The system uses accelerometers and magnetic sensors in smartphones without pre-installed infrastructure. We reduced the cumulative error of location tracking by geo-magnetic observations at corners and spots with magnetic fluctuations. In addition, we developed a robust estimation model that is tolerant to false positives, as well as a mobility model that reflects the characteristics of multiple sensors. Extensive evaluation in a real environment indicates that our system is accurate and cost-effective.

Research of indoor mobile biological air purifier pedestrian tracking system

2016 ◽  
Author(s):  
Liang Fan ◽  
Chen Hongdou ◽  
Dai Fenghui ◽  
Cui Shigang ◽  
Wang Tianpeng ◽  
...  
Keyword(s):  
Tracking System ◽  
Pedestrian Tracking ◽  
Air Purifier

A Real-Time Active Pedestrian Tracking System Inspired by the Human Visual System

2015 ◽  
Vol 8 (1) ◽  
pp. 39-51 ◽  
Author(s):  
Yuxia Wang ◽  
Qingjie Zhao ◽  
Bo Wang ◽  
Shixian Wang ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Visual System ◽  
Real Time ◽  
Human Visual System ◽  
Tracking System ◽  
Pedestrian Tracking

scholarly journals Bayesian Estimation-Based Pedestrian Tracking in Microcells

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yoshiaki Taniguchi ◽  
Masahiro Sasabe ◽  
Satoshi Aihara ◽  
Hirotaka Nakano
Keyword(s):  
Time Series ◽  
Combinatorial Optimization ◽  
Bayesian Estimation ◽  
Tracking System ◽  
Mobility Model ◽  
Sensor Nodes ◽  
Video Sequences ◽  
Pedestrian Tracking ◽  
Tracking Method ◽  
Success Ratio

We consider a pedestrian tracking system where sensor nodes are placed only at specific points so that the monitoring region is divided into multiple smaller regions referred to as microcells. In the proposed pedestrian tracking system, sensor nodes composed of pairs of binary sensors can detect pedestrian arrival and departure events. In this paper, we focus on pedestrian tracking in microcells. First, we investigate actual pedestrian trajectories in a microcell on the basis of observations using video sequences, after which we prepare a pedestrian mobility model. Next, we propose a method for pedestrian tracking in microcells based on the developed pedestrian mobility model. In the proposed method, we extend the Bayesian estimation to account for time-series information to estimate the correspondence between pedestrian arrival and departure events. Through simulations, we show that the tracking success ratio of the proposed method is increased by 35.8% compared to a combinatorial optimization-based tracking method.

A Robust Indoor Pedestrian Tracking System with Sparse Infrastructure Support

2013 ◽  
Vol 12 (7) ◽  
pp. 1392-1403 ◽  
Author(s):  
Yunye Jin ◽  
Wee-Seng Soh ◽  
Mehul Motani ◽  
Wai-Choong Wong
Keyword(s):  
Tracking System ◽  
Pedestrian Tracking ◽  
Indoor Pedestrian Tracking

New Drift Reset Method for Pedestrian Tracking with a Low-Cost IMU

2013 ◽  
Vol 284-287 ◽  
pp. 2176-2180 ◽  
Author(s):  
Yao Tung Chuang ◽  
Cheng Ta Shen ◽  
Yi Lin Hsu ◽  
Sheng Wen Shih
Keyword(s):  
Inertial Measurement Unit ◽  
Temperature Compensation ◽  
Tracking System ◽  
Low Cost ◽  
Measurement Unit ◽  
Position Tracking ◽  
Pedestrian Tracking ◽  
Inertial Measurement ◽  
Rate Gyro ◽  
Global Reference Frame

In this work, we study the pedestrian position tracking problem using a foot-mounted inertial measurement unit (IMU). The IMU consists of a tri-axis rate-gyro, a tri-axis accelerometer and a tri-axis magnetometer. The magnetometer is used for constructing a global reference frame at the initial phase. The pedestrian orientation and position are estimated by integrating signals of the rate-gyro and the accelerometer. Since the integration operation usually introduces unbounded drift errors, a new drift reset method derived from a constant-ground-normal condition is proposed to compensate for the accumulated drift error. Furthermore, a temperature compensation (TC) method is described which can alleviate the rate-gyro error due to temperature variation. Real experiments have been conducted with six subjects to test the performance of the proposed method and the results show the promising performance of the proposed tracking system.

Sign in / Sign up

Export Citation Format

Share Document