William Marsh Rice University

Carnegie Mellon University

Mitsubishi Electric Research Laboratories, Inc.

Samsung Electronics Co., Ltd.

Aswin C Sankaranarayanan

Ashok Veeraraghavan

Richard G Baraniuk

Amit Kumar Agrawal

Oncel C Tuzel

Christoph Emanuel Studer

Jianing Shi

Yicheng Wu

Vivek Boominathan

Huaijin Chen

Jian Jim Wang

Hyong Euk Lee

William L Whittaker

Srinivasa Narasimhan

Eunhee Kang

Joseph Bartels

Anqi Yang

Lisa A Hendricks

Ali Ayremlou

M Salman Asif

A device with image acquisition includes: a first phase mask disposed at a front end of a display layer and configured to modulate external light; the display layer comprising pixel areas between hole areas through which the modulated light that has passed through the first phase mask passes; a second phase mask disposed at a rear end of the display layer and configured to modulate the modulated light that has passed through the first phase mask; an image sensor disposed at a rear end of the second phase mask and configured to generate a raw image by sensing the modulated light that has passed through the second phase mask; and a processor configured to perform image processing on the raw image, based on blur information corresponding to the raw image.

Method and apparatus with image quality improvement

A method for a passive single-viewpoint 3D imaging system comprises capturing an image from a camera having one or more phase masks. The method further includes using a reconstruction algorithm, for estimation of a 3D or depth image.

Passive and single-viewpoint 3D imaging system

Embodiments described herein are generally directed to a device that monitors for the presence of objects passing through or impinging on a virtual shell near the device, referred to herein as a 'light curtain', which is created by rapidly rotating a line sensor and a line laser in synchrony. The boundaries of the light curtain are defined by a sweeping line defined by the intersection of the sensing and illumination planes.

Programmable light curtains

A lens-free imaging system for generating an image of a scene includes an electromagnetic (EM) radiation sensor; a mask disposed between the EM radiation sensor and the scene; an image processor that obtains signals from the EM radiation sensor while the EM radiation sensor is exposed to the scene; and estimates the image of the scene based on, at least in part, the signals and a transfer function between the scene and the EM radiation sensor.

Lensless imaging system using an image sensor with one or more attenuating layers

A compressive sensing system for dynamic video acquisition. The system includes a video signal interface including a compressive imager configured to acquire compressive sensed video frame data from an object, a video processing unit including a processor and memory. The video processing unit is configured to receive the compressive sensed video frame data from the video signal interface. The memory comprises computer readable instructions that when executed by the processor cause the processor to generate a motion estimate from the compressive sensed video frame data and generate dynamical video frame data from the motion estimate and the compressive sensed video frame data. The dynamical video frame data may be output.

Methods and systems for video compressive sensing for dynamic imaging

A new framework for video compressed sensing models the evolution of the image frames of a video sequence as a linear dynamical system (LDS). This reduces the video recovery problem to first estimating the model parameters of the LDS from compressive measurements, from which the image frames are then reconstructed. We exploit the low-dimensional dynamic parameters (state sequence) and high-dimensional static parameters (observation matrix) of the LDS to devise a novel compressive measurement strategy that measures only the dynamic part of the scene at each instant and accumulates measurements over time to estimate the static parameters. This enables us to lower the compressive measurement rate considerably yet obtain video recovery at a high frame rate that is in fact inversely proportional to the length of the video sequence. This property makes our framework well-suited for high-speed video capture and other applications. We validate our approach with a range of experiments including classification experiments that highlight the purposive nature of our framework.

Method and apparatus for compressive acquisition and recovery of dynamic imagery

A point correspondence procedure is applied to a set of images of a specular object to produce sparse reflection correspondences. The set of images is subject to rotation while acquired by a camera. That is, either the camera, the environment or the object rotates. Either a linear system A&#x398;=0 is solved or a related second order cone program (SOCP) is solved, where &#x398; is a vector of local surface parameters. Gradients of the surface are obtained from the local quadric surface parameters, and the gradients are integrated to obtain normals, wherein the normals define a shape of the surface.

Method for reconstructing surfaces of specular object from sparse reflection correspondences

Embodiments of the invention disclose a system and a method for determining points of parabolic curvature on a surface of a specular object from a set of images of the object is acquired by a camera under a relative motion between a camera-object pair and the environment. The method determines directions of image gradients at each pixel of each image in the set of images, wherein pixels from different images corresponding to an identical point on the surface of the object form corresponding pixels. The corresponding pixels having substantially constant the direction of the image gradients are selected as pixels representing points of the parabolic curvature.

Determining points of parabolic curvature on surfaces of specular objects

Growing community of inventors

Pittsburgh, PA, United States of America

Aswin C Sankaranarayanan