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Book ChapterDOI

Pano UMECHIKA: A Crowded Underground City Panoramic View System

TLDR
This work proposes a method which simultaneously subtracts pedestrians based on background subtraction method and generates location metadata by manually input from maps and achieved an underground panoramic view system which displays no pedestrians.
Abstract
Toward a really useful navigation system, utilizing spherical panoramic photos with maps like Google Street View is efficient. Users expect the system to be available in all areas they go. Conventional shooting methods obtain the shot position from GPS sensor. However, indoor areas are out of GPS range. Furthermore, most urban public indoor areas are crowded with pedestrians. Even if we blur the pedestrians in a photo, the photos with blurring are not useful for scenic information. Thus, we propose a method which simultaneously subtracts pedestrians based on background subtraction method and generates location metadata by manually input from maps. Using these methods, we achieved an underground panoramic view system which displays no pedestrians.

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Citations
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AR Using Pre-captured Images Considering Illumination of Real Scene

TL;DR: This paper proposes a novel pre-captured AR system considering the change of real-world illumination, which shows user perspective images generated from omnidirectional AR images based on the estimated pose of the mobile device.
Patent

Method and system for the virtual tour of inaccessible and/or impassable places with vehicles

TL;DR: In this paper, the authors propose a virtual tour of inaccessible and/or impassable places with vehicles, which comprises the steps of: providing a route within a places; providing portable acquisition means (1), which are able to cyclically acquire photographic images of the surrounding environment; walking along the route carrying the acquisition means, so that they acquire the photographic images relating to a plurality of points along a route; processing the images relative to each of the points so as to define respective pans; processing pans by means of a viewing software, and providing one or more content files which include
Proceedings ArticleDOI

Sensor based operation of Google Street View in iPad

TL;DR: This work proposes the operation of viewer based on the viewpoint tracking and heading angle of iPad so that the virtual walk behavior is realized by the moving the user's gaze point and leaning the iPad.
References
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Journal ArticleDOI

Distinctive Image Features from Scale-Invariant Keypoints

TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Journal ArticleDOI

Speeded-Up Robust Features (SURF)

TL;DR: A novel scale- and rotation-invariant detector and descriptor, coined SURF (Speeded-Up Robust Features), which approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.
Proceedings ArticleDOI

The anatomy of a context-aware application

TL;DR: A sensor-driven, or sentient, platform for context-aware computing that enables applications to follow mobile users as they move around a building and presents it in a form suitable for application programmers is described.
Journal ArticleDOI

Google Street View: Capturing the World at Street Level

TL;DR: A team of Google researchers describes the technical challenges involved in capturing, processing, and serving street-level imagery on a global scale.
Proceedings ArticleDOI

Accuracy characterization for metropolitan-scale Wi-Fi localization

TL;DR: This work evaluates the feasibility of building a wide-area 802.11 Wi-Fi-based positioning system, and shows that it can estimate a user's position with a median positioning error of 13-40 meters, lower than existing positioning systems.
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