The mobile phone as a platform for assisting the independent living ...

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1. Create database with images and tag them manually2. Take a query image and send it to the server3. Compare it with the images stored in the database, using off-the-shelvealgorithms for image comparison4. Each algorithm assigns a weight to every image in the database which reflects thedegree of similarity5. If the weight of the best match is less than a certain threshold, discard the queryimage6. Else return the location of the image that matches the query image withmaximum weightThe first step belongs to the training stage of the fingerprinting technique, whereas therest steps to the matching stage.6.4.1 Training stageTo have better results, it is important to build an extensive database of images. A C#client runs on the phone and captures photographs (Fig. 9) periodically as the mobileuser walks around and then sends the images to a web server through FTP.Fig. 9: Examples of photographs used in the training stageThe images are tagged with location manually afterwards and their location informationalong with some of their EXIF metadata is stored in a database (Fig. 10).35
Fig. 10: The database table that stores the image informationTo facilitate the tagging process, we decided that it would be more convenient to tag animage with the exact location on a house map rather than with a descriptive sentence.For that reason we constructed a house map of the apartment and we built anapplication where the user can click with his mouse at the exact location to tag an image.The location stored in the database is in the form of Cartesian coordinates (X,Y)referring to the house map area. An example of this application is shown in Fig. 10.Fig. 11: The tagging process36
Page 1: ATHENS UNIVERSITY OF ECONOMICS AND
Page 5 and 6: AbstractMobile phones or Personal D
Page 7 and 8: Chapter 7: Implementation of an app
Page 9 and 10: List of TablesTable 1: Advantages a
Page 11 and 12: suffering from memory and orientati
Page 13 and 14: Chapter 2Smart Homes2.1 Smart Homes
Page 15 and 16: • Automate specific tasks that a
Page 17 and 18: Fig. 1: A smart home solution 1It i
Page 19 and 20: lighting strips and passive infra-r
Page 21 and 22: The Amigo project [10] is a joint e
Page 23 and 24: However, inside a building, that un
Page 25 and 26: with co-ordinates in the form of la
Page 27 and 28: At last, the utilized technology mu
Page 29 and 30: In this work we concentrate on achi
Page 31 and 32: In order to estimate the user locat
Page 33 and 34: 4.2.1 Cell-based methodsCell-based
Page 35 and 36: correlation between distance and si
Page 37 and 38: thus increasing the storage and mem
Page 39 and 40: egions. Examining images based on t
Page 41 and 42: Chapter 6Implementation of an indoo
Page 43: 6.3 Experimental environment, hardw
Page 47 and 48: Fig.12: The matching stageThe query
Page 49 and 50: 6.6 Future workIn this section we p
Page 51 and 52: According to the Eye Diseases Preva
Page 53 and 54: Fig. 14: Use of image processing te
Page 55 and 56: list, printing the best match as th
Page 57 and 58: Chapter 8Conclusion8.1 ConclusionMo
Page 59 and 60: [13] Gilles Virone, Norbert Noury,
Page 61 and 62: [40] Andrew M. Ladd, Kostas E. Bekr
Page 63: [65] X. Chen and A.L. Yuille, “A

The mobile phone as a platform for assisting the independent living ...

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