Looking around the corner using transient imaging

Kirmani, Ahmed; Hutchison, Tyler; Davis, James; Raskar, Ramesh

doi:10.1109/iccv.2009.5459160

Cited by 167 publications

(112 citation statements)

References 15 publications

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“…Time-gated viewing using mirror reflections allows imaging around corners, for example, from a glass window [6][7][8] . Three bounce analysis of a time-of-flight camera can recover hidden 1-0-1 planar barcodes 9,10 but the technique assumes well-separated, isolated hidden patches with known correspondence between hidden patches and recorded pulses. Similar to these and other inverse light transport approaches 11 , we use a light source to illuminate one scene spot at a time and record the reflected light after its interaction with the scene.…”

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confidence: 99%

Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging

et al. 2012

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The recovery of objects obscured by scattering is an important goal in imaging and has been approached by exploiting, for example, coherence properties, ballistic photons or penetrating wavelengths. Common methods use scattered light transmitted through an occluding material, although these fail if the occluder is opaque. Light is scattered not only by transmission through objects, but also by multiple reflection from diffuse surfaces in a scene. This reflected light contains information about the scene that becomes mixed by the diffuse reflections before reaching the image sensor. This mixing is difficult to decode using traditional cameras. Here we report the combination of a time-of-flight technique and computational reconstruction algorithms to untangle image information mixed by diffuse reflection. We demonstrate a three-dimensional range camera able to look around a corner using diffusely reflected light that achieves sub-millimetre depth precision and centimetre lateral precision over 40 cm× 40 cm×40 cm of hidden space.

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Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging

et al. 2012

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“…way to capture these high speed dynamics is to raise the frame rate via new camera elements; a representative work on the capture of super-high speed dynamics was proposed by Kirmani et al [124], who used a femtosecond laser and an ultrafast photodetector array to record the light path and infer the scene structure, as illustrated in Figure 5(a). Another way is to encode the high frequency information of the moving objects or the relative motion between the camera and the scene in some sense, and perform better restoration.…”

Section: Temporal Resolutionmentioning

confidence: 99%

An overview of computational photography

Suo

Dai

2012

Sci. China Inf. Sci.

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Computational photography is an emerging multidisciplinary field. Over the last two decades, it has integrated studies across computer vision, computer graphics, signal processing, applied optics and related disciplines. Researchers are exploring new ways to break through the limitations of traditional digital imaging for the benefit of photographers, vision and graphics researchers, and image processing programmers. Thanks to much effort in various associated fields, the large variety of issues related to these new methods of photography are described and discussed extensively in this paper. To give the reader the full picture of the voluminous literature related to computational photography, this paper briefly reviews the wide range of topics in this new field, covering a number of different aspects, including: (i) the various elements of computational imaging systems and new sampling and reconstruction mechanisms; (ii) the different image properties which benefit from computational photography, e.g. depth of field, dynamic range; and (iii) the sampling subspaces of visual scenes in the real world. Based on this systematic review of the previous and ongoing work in this field, we also discuss some open issues and potential new directions in computational photography. This paper aims to help the reader get to know this new field, including its history, ultimate goals, hot topics, research methodologies, and future directions, and thus build a foundation for further research and related developments.

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“…We assume that the position, orientation, and dimensions ( -by-) of the planar surface are known. Estimation of these geometric parameters using diffuse illumination and time-resolved sensing was recently demonstrated [6]. Formation of an ideal gray scale image is the recovery of the reflectance pattern on the surface, which can be modeled as a 2-D function .…”

Section: Scene Response To Impulsive Illuminationmentioning

confidence: 99%

Diffuse Imaging: Creating Optical Images With Unfocused Time-Resolved Illumination and Sensing

Kirmani

Jeelani

Montazerhodjat

et al. 2012

IEEE Signal Process. Lett.

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Abstract-Conventional imaging uses steady-state illumination and light sensing with focusing optics; variations of the light field with time are not exploited. We develop a signal processing framework for estimating the reflectance of a Lambertian planar surface in a known position using omnidirectional, time-varying illumination and unfocused, time-resolved sensing in place of traditional optical elements such as lenses and mirrors. Our model associates time sampling of the intensity of light incident at each sensor with a linear functional of . The discrete-time samples are processed to obtain -regularized estimates of . Improving on previous work, using nonimpulsive, bandlimited light sources instead of impulsive illumination significantly improves signal-tonoise ratio (SNR) and reconstruction quality. Our simulations suggest that practical diffuse imaging applications may be realized with commercially-available temporal light intensity modulators and sensors used in standard optical communication systems.

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Looking around the corner using transient imaging

Abstract: We show that multi-path analysis using images from a timeof-flight (ToF)

Cited by 167 publications

References 15 publications

Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging

Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging

An overview of computational photography

Diffuse Imaging: Creating Optical Images With Unfocused Time-Resolved Illumination and Sensing

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