Learning landmark salience models from users’ route instructions
| Autor: | Johan Boye, Jana Götze |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Landmark
Computer Networks and Communications business.industry Computer science Feature vector ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies 02 engineering and technology Machine learning computer.software_genre Pedestrian navigation Salient Salience (neuroscience) Ranking SVM Signal Processing 0202 electrical engineering electronic engineering information engineering Information system 020201 artificial intelligence & image processing Weight Artificial intelligence Electrical and Electronic Engineering business computer 021101 geological & geomatics engineering |
| Zdroj: | Journal of Location Based Services. 10:47-63 |
| ISSN: | 1748-9733 1748-9725 |
| DOI: | 10.1080/17489725.2016.1172739 |
| Popis: | Route instructions for pedestrians are usually better understood if they include references to landmarks, and moreover, these landmarks should be as salient as possible. In this paper, we present an approach for automatically deriving a mathematical model of salience directly from route instructions given by humans. Each possible landmark that a person can refer to in a given situation is modelled as a feature vector, and the salience associated with each landmark can be computed as a weighted sum of these features. We use a ranking SVM method to derive the weights from route instructions given by humans as they are walking the route. The weight vector, representing the person’s personal salience model, determines which landmarks are most appropriate to refer to in new situations. |
| Databáze: | OpenAIRE |
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