Estimating Geo-temporal Location of Stationary Cameras Using Shadow Trajectories

Junejo, Imran N.; Foroosh, Hassan

doi:10.1007/978-3-540-88682-2_25

Cited by 51 publications

(25 citation statements)

References 16 publications

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“…Imaged solar shadows have close relationships not only with camera parameters but also with various scene informations like where and when the image is taken. Among these, geolocation is one of the most fundamentals [16,26,27]. Wu et al [16] investigate the property of solar shadow trajectories on a planar surface and show that camera parameters, latitude, longitude, and the height ratios of shadow casting objects can be estimated from two observed shadow trajectories.…”

Section: Related Work and Main Contributionmentioning

confidence: 99%

Image composite authentication using a single shadow observation

Cao

Zhao²,

Wang

et al. 2015

Sci. China Inf. Sci.

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The paper presents a novel method for image composite authentication based on a single shadow in an outdoor image. Existing methods based on the shadow geometry consistency involve more than two shadow observations. We relax the requirement of two shadow observations in the same scene. As a trade-off, we use the information in EXIF (Exchangeable Image File) based on which the ground truth sun elevation is calculated. We also estimate the sun elevation based on geometric constraints the scene provides, whose consistency serves as the cue to authenticate image forgery. It is the first attempt, to our best knowledge, to make use of sun elevation with shadow of one object to authenticate outdoor images. Also, the novel use of GPS (Global Positioning System), and Date and Time data of captured image makes image forensics possible even in one image containing a single shadow. Experimental results on both the synthetic data and visually plausible images demonstrate the performance of the proposed method.

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Section: Related Work and Main Contributionmentioning

confidence: 99%

Image composite authentication using a single shadow observation

Cao

Zhao²,

Wang

et al. 2015

Sci. China Inf. Sci.

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“…Junejo and Foroosh [15] calibrate the intrinsic parameters of a camera and solve for constraints on camera geo-location from the trajectories of shadows of two points moving across a ground plane, and Wu et. al [24] extend this to complete camera calibration, geolocation, and the relative heights of the two shadow casting points, even if those are not in the field of view.…”

Section: Related Workmentioning

confidence: 99%

Structure from shadow motion

Abrams

Schillebeeckx

Pless

2014

2014 IEEE International Conference on Computational Photography (ICCP)

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In outdoor images, cast shadows define 3D constraints between the sun, the points casting a shadow, and the surfaces onto which shadows are cast. This cast shadow structure provides a powerful cue for 3D reconstruction, but requires that shadows be tracked over time, and this is difficult as shadows have minimal texture. Thus, we develop a shadow tracking system that enforces geometric consistency for each track and then combines thousands of tracking results to create a 3D model of scene geometry. We demonstrate reconstruction results on a variety of outdoor scenes, including some that show the 3D structure of occluders never directly observed by the camera.

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“…This information in combination with time stamps is sufficient for the recovery of the geolocation of the sequence. A similar path is taken in [9].…”

Section: Prior Artmentioning

confidence: 99%

Multimodal location estimation

Friedland

Vinyals

Darrell

2010

Proceedings of the 18th ACM International Conference on Multimedia

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In this article we define a multimedia content analysis problem, which we call multimodal location estimation: Given a video/image/audio file, the task is to determine where it was recorded. A single indication, such as a unique landmark, might already pinpoint a location precisely. In most cases, however, a combination of evidence from the visual and the acoustic domain will only narrow down the set of possible answers. Therefore, approaches to tackle this task should be inherently multimedia. While the task is hard, in fact sometimes unsolvable, training data can be leveraged from the Internet in large amounts. Moreover, even partially successful automatic estimation of location opens up new possibilities in video content matching, archiving, and organization. It could revolutionize law enforcement and computer-aided intelligence agency work, especially since both semi-automatic and fully automatic approaches would be possible. In this article, we describe our idea of growing multimodal location estimation as a research field in the multimedia community. Based on examples and scenarios, we propose a multimedia approach to leverage cues from the visual and the acoustic portions of a video as well as from given metadata. We also describe experiments to estimate the amount of available training data that could potentially be used as publicly available infrastructure for research in this field. Finally, we present an initial set of results based on acoustic and visual cues and discuss the massive challenges involved and some possible paths to solutions.

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Estimating Geo-temporal Location of Stationary Cameras Using Shadow Trajectories

Cited by 51 publications

References 16 publications

Image composite authentication using a single shadow observation

Image composite authentication using a single shadow observation

Structure from shadow motion

Multimodal location estimation

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