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Book ChapterDOI

Pano UMECHIKA: A Crowded Underground City Panoramic View System

TL;DR: 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.
Citations
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Proceedings ArticleDOI
19 Nov 2013
TL;DR: This work developed a mobile AR system in a significantly different way from conventional systems, in this system, captured omnidirectional images and virtual objects are registered geometrically and photometricrically in an offline rendering process.
Abstract: In the field of augmented reality (AR), geometric and photometric registration is routinely achieved in real time. However, real-time geometric registration often leads to misalignment (e.g., jitter and drift) due to the error from camera pose estimation. Due to limited resources on mobile devices, it is also difficult to implement state-of-the-art techniques for photometric registration on mobile AR systems. In order to solve these problems, we developed a mobile AR system in a significantly different way from conventional systems. In this system, captured omnidirectional images and virtual objects are registered geometrically and photometrically in an offline rendering process. The appropriate part of the prerendered omnidirectional AR image is shown to a user through a mobile device with online registration between the real world and the pre-captured image. In order to investigate the validity of our new framework for mobile AR, we conducted experiments using the prototype system on a real site in Todai-ji Temple, a famous world cultural heritage site in Japan.

6 citations

Proceedings ArticleDOI
01 Sep 2014
TL;DR: This paper proposes a novel IAR system which reflects real-world illumination change by selecting an appropriate image from a set of images pre-captured under various illumination, and shows that the proposed system can improve the realism in IAR.
Abstract: ISMAR 2014 : IEEE and ACM International Symposium on Mixed and Augmented Reality , Sep 10-12, 2014 , Munich, Germany

5 citations


Cites methods from "Pano UMECHIKA: A Crowded Undergroun..."

  • ...Omnidirectional images without dynamic objects are generated from the input videos using a panoramic photography approach for crowded environments [2]....

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Dissertation
01 Jan 2017
TL;DR: In this paper, the authors proposed a technique for the detection of video inpainting forgery based on the statistical correlation of hessian matrix features extracted from the suspected video.
Abstract: The use of digital videos in criminal investigation and civil litigation has become popular, this is due to the advancement of embedded cameras in handheld devices such as mobile phones, PDA’s and tablets. However, the content of digital videos can be extracted, enhanced and modified using inexpensive and user friendly video editing software, such as; Adobe Photoshop, Sefexa, etc. Thus, the influx of these video editing softwarelead to the creation of serious problems that are associated with the authenticity of digital videos by making their validity questionable. In order to address these problems, two approaches for the authentication of digital videos were proposed by digital forensic researchers. The approaches are either active or passive. Active approaches are the earliest form of video authentication techniques; an active approach is based on digital watermark technology that is used for video authentication and ownership verification. A digital watermark is a hidden digital marker embedded in a noise tolerant video signal. However, the problem with the active approach to video authentication is that it can only be applied in limited situations and it requires the use of a special hardware. Moreover, an authorized person responsible for the watermark insertion can tamper with the video before inserting the digital watermark. Furthermore, techniques for encryption can be used to prevent an unauthorized person from tampering with the content of the video, however, these encryption techniques donot prevent the file owner from tampering with his own video. This limits the ability of digital watermark to ensure authenticity in digital videos. In response to these limitations, passive approaches were introduced. Passive approaches rely on the behaviour of features embedded in a video for forgery detection purposes. Thus, the aim of this doctoral study as a contribution to the field of digital forensic is to develop techniques based on selected video features that can be used to detect tampering of a digital video. In this study, passive forensic techniques are proposed to detect (1) Digital video inpainting forgery, and (2) Chroma key forgery in digital videos. Each of these techniques focus on the specific features that can be used to detect that kind of forgery. Firstly, a technique for the detection of video inpainting forgery is proposed using the statistical correlation of hessian matrix features extracted from the suspected video. Secondly, another technique is proposed for the detection of chroma key forgery in a digital video using the statistical correlation of blurring features extracted from the suspected video. Results from these experiments conducted have proven that hessian matrix features can effectively be used to detect video inpainting forgery with 99.79% accuracy whilst the blurring feature can effectively detect chroma key forgery in digital videos with 99.12% accuracy.

3 citations


Cites background from "Pano UMECHIKA: A Crowded Undergroun..."

  • ...Structural inpainting algorithms have recorded a great success in variety of applications such as editing images during image retouching, object removal from images and video for privacy protection (Arai et al., 2010)....

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Journal ArticleDOI
TL;DR: Experimental results show the proposed method is capable of preserving the underlying structure in the missing region, while achieving more than 5 times faster computational speed than the state-of-the-art inpainting method.
Abstract: This paper presents a novel inpainting method based on structure estimation. The method first estimates an initial image that captures the rough structure and colors in the missing region. This image is generated by probabilistically estimating the gradient within the missing region based on edge segments intersecting its boundary, and then by flooding the colors on the boundary into the missing region. The color flooding is formulated as an energy minimization problem, and is efficiently optimized by the conjugate gradient method. Finally, by locally replacing the missing region with local patches similar to both the adjacent patches and the initial image, the inpainted image is synthesized. The initial image not only serves as a guide to ensure the underlying structure is preserved, but also allows the patch selection process to be carried out in a greedy manner, which leads to substantial speedup. Experimental results show the proposed method is capable of preserving the underlying structure in the missing region, while achieving more than 5 times faster computational speed than the state-of-the-art inpainting method. Subjective evaluation of image quality also shows the proposed method outperforms the previous methods. key words: image inpainting, image completion, texture synthesis, image structure

3 citations


Cites methods from "Pano UMECHIKA: A Crowded Undergroun..."

  • ..., an image editing tool for photo retouching and removing pedestrians from street images for privacy protection [2]....

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Journal ArticleDOI
TL;DR: This paper proposes a novel IAR system that reflects real-world illumination changes by selecting an appropriate image from among multiple pre-captured images obtained under various illumination conditions, and shows that the consideration of real- world illumination changes improves the realism of the IAR experience.
Abstract: Indirect augmented reality (IAR) employs a unique approach to achieve high-quality synthesis of the real world and the virtual world, unlike traditional augmented reality (AR), which superimposes virtual objects in real time. IAR uses pre-captured omnidirectional images and offline superimposition of virtual objects for achieving jitter- and drift-free geometric registration as well as high-quality photometric registration. However, one drawback of IAR is the inconsistency between the real world and the pre-captured image. In this paper, we present a new classification of IAR inconsistencies and analyze the effect of these inconsistencies on the IAR experience. Accordingly, we propose a novel IAR system that reflects real-world illumination changes by selecting an appropriate image from among multiple pre-captured images obtained under various illumination conditions. The results of experiments conducted at an actual historical site show that the consideration of real-world illumination changes improves the realism of the IAR experience.

3 citations

References
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Journal ArticleDOI
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.
Abstract: 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. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability against a large database of features from many images. This paper also describes an approach to using these features for object recognition. The recognition proceeds by matching individual features to a database of features from known objects using a fast nearest-neighbor algorithm, followed by a Hough transform to identify clusters belonging to a single object, and finally performing verification through least-squares solution for consistent pose parameters. This approach to recognition can robustly identify objects among clutter and occlusion while achieving near real-time performance.

46,906 citations

Journal ArticleDOI
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.

12,449 citations

Proceedings ArticleDOI
01 Aug 1999
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.
Abstract: We describe a sensor-driven, or sentient, platform for context-aware computing that enables applications to follow mobile users as they move around a building. The platform is particularly suitable for richly equipped, networked environments. The only item a user is required to carry is a small sensor tag, which identifies them to the system and locates them accurately in three dimensions. The platform builds a dynamic model of the environment using these location sensors and resource information gathered by telemetry software, and presents it in a form suitable for application programmers. Use of the platform is illustrated through a practical example, which allows a user's current working desktop to follow them as they move around the environment.

1,479 citations

Journal ArticleDOI
TL;DR: A team of Google researchers describes the technical challenges involved in capturing, processing, and serving street-level imagery on a global scale.
Abstract: Street View serves millions of Google users daily with panoramic imagery captured in hundreds of cities in 20 countries across four continents. A team of Google researchers describes the technical challenges involved in capturing, processing, and serving street-level imagery on a global scale.

693 citations

Proceedings ArticleDOI
06 Jun 2005
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.
Abstract: Location systems have long been identified as an important component of emerging mobile applications. Most research on location systems has focused on precise location in indoor environments. However, many location applications (for example, location-aware web search) become interesting only when the underlying location system is available ubiquitously and is not limited to a single office environment. Unfortunately, the installation and calibration overhead involved for most of the existing research systems is too prohibitive to imagine deploying them across, say, an entire city. In this work, we evaluate the feasibility of building a wide-area 802.11 Wi-Fi-based positioning system. We compare a suite of wireless-radio-based positioning algorithms to understand how they can be adapted for such ubiquitous deployment with minimal calibration. In particular, we study the impact of this limited calibration on the accuracy of the positioning algorithms. Our experiments show that we can estimate a user's position with a median positioning error of 13-40 meters (depending upon the characteristics of the environment). Although this accuracy is lower than existing positioning systems, it requires substantially lower calibration overhead and provides easy deployment and coverage across large metropolitan areas.

562 citations