1 Overview of the Project
Space in total | 4,3 km\(^2\) |
Length of all paths | 110 km |
Doors | 1.563 |
Elevators | 320 |
Stairs | 151 |
2 Components of the System
2.1 URWalking Web Server
2.2 Web Application
2.3 Android Application
2.4 Data for Indoor Navigation
3 Applications in Research Contexts
3.1 Data Driven Validation of Wayfinding Models
3.2 Real-Time Prediction of Areas of Interest
Class label | Object confidence | Class accuracy |
---|---|---|
Train | 0.36 | 0.85 |
Person | 0.64 | 0.82 |
Dog | 0.47 | 0.80 |
Diningtable | 0.27 | 0.74 |
Refrigerator | 0.53 | 0.71 |
Chair | 0.18 | 0.68 |
Laptop | 0.81 | 0.67 |
Bed | 0.44 | 0.64 |
Book | 0.31 | 0.59 |
Bus | 0.14 | 0.59 |
Cell phone | 0.84 | 0.58 |
Tvmonitor | 0.70 | 0.56 |
Cat | 0.20 | 0.53 |
Clock | 0.77 | 0.48 |
Keyboard | 0.90 | 0.44 |
Horse | 0.27 | 0.43 |
Bench | 0.11 | 0.39 |
Tie | 0.13 | 0.36 |
Remote | 0.14 | 0.32 |
Sofa | 0.10 | 0.27 |
Car | 0.26 | 0.16 |
Umbrella | 0.25 | 0.12 |
3.3 Prediction of Landmark Salience from Gaze Data
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\(PS>1\): the degree of focal processing in the environment is higher than that on the display. For the current routing instruction, the test person can focus his/her attention on few objects in the environment and does not need much effort to explore the environment to find the landmark referred to in the instruction.
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\(PS\le 1\): the degree to focal processing in the environment is low in relation to that on the display. So, proportionally, test persons need more ambient processing to explore the environment in order to eventually locate the referred landmark.