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Title: Autobus: Selection of Passenger Seats Based on Viewing Experience for Touristic Tours
Authors: SAMSONOV, Pavel 
HELLER, Florian 
Schöning, Johannes
Issue Date: 2017
Publisher: ACM
Source: Proceedings of 16th International Conference on Mobile and Ubiquitous Multimedia MUM 2017, ACM,p. 1-7
Abstract: Choosing a seat for traveling can be a complex evaluation of constraints depending on personal preferences. There are websites that help to choose the best seat in a bus, in a train, or on an airplane. However, these recommendations only consider seat-related factors and not the view from the window. While a scenic view rarely influences the decision for a seat on a plane, it is much more important for train rides and especially for scenic bus tours. Therefore, travel website users often discuss which side offers the best view on a specific trip. We propose an algorithm, which decides on which side of the road the view is the most scenic based on Google Street View images. These results can be used by travelers to choose a seat and by scenic tour providers to balance the scenic views between sides or add options during checkout
Keywords: machine learning; Google Street View; scenic Routes
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ISBN: 9781450353786
DOI: 10.1145/3152832.3152846
ISI #: 000463850100036
Rights: 2017 Copyright held by the owner/author(s). Publication rights licensed to ACM.
Category: C1
Type: Proceedings Paper
Validations: vabb 2020
Appears in Collections:Research publications

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