Sony Corporation

Ut-battelle, Inc.

Sony Electronics Inc

The University of Tennessee Research Foundation

Xiaoling Wang

Alexander Berestov

Jianing Wei

Xue Tu

Takami Mizukura

Elias Stanley Greenbaum

Miguel Rodriguez, Jr

Hairong Qi

Naoya Katoh

Farhan A Baqai

Chuen-Chien Lee

Naoya Kato

A method for converting a 2D image into a 3D image includes receiving the 2D image; determining whether the received 2D image is a portrait, wherein the portrait can be a face portrait or a non-face portrait; if the received 2D image is determined to be a portrait, creating a disparity between a left eye image and a right eye image based on a local gradient and a spatial location; generating the 3D image based on the created disparity; and outputting the generated 3D image.

Methods and systems for 2D to 3D conversion from a portrait image

A method for converting a 2D image into a 3D image includes receiving the 2D image; analyzing content of the received 2D image; determining a 2D-to-3D image conversion method based on a result of the content analysis; generating the 3D image by applying the determined method to the received 2D image; and providing the generated 3D image.

2D to 3D image conversion based on image content

A system for biosensor-based detection of toxins includes providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

Biosensor method and system based on feature vector extraction

A method for generating a depth map for a 2D image includes receiving the 2D image; analyzing content of the received 2D image; determining a depth map based on a result of the content analysis; refining the determined depth map using an edge-preserving and noise reducing smoothing filter; and providing the refined depth map.

Fast depth map generation for 2D to 3D conversion

Improving color calibration, and similar operations, by generating an optimal raw RGB color chart, in the raw RGB domain, for an imaging device with a given type of image sensor, such as for a digital still camera. Calibration is performed in response to a constraint which takes into account the spectral sensitivity of the image sensor used on the camera as well as spectral reflectance and spectral radiance of multiple illuminants. Calibration is performed using the raw RGB color chart which is illuminant independent and image sensor specific and which can match the calibration performance of known calibration standards, such as Macbeth 24.

Optimal raw RGB determination for color calibration

A method of biosensor-based detection of toxins comprises the steps of providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

A signal processing system includes: defining a nonlinear function; defining a set of requirements for an output signal; obtaining an input signal; applying a cubic polynomial fitting to approximate the nonlinear function and provide an approximated nonlinear function; assigning a set of fitted polynomial parameters to the approximated nonlinear function; transforming the input signal with the approximated nonlinear function to provide a transformed signal; modifying the transformed signal by adjusting the set of fitted polynomial parameters to provide a modified signal meeting the set of requirements for the output signal; and outputting the modified signal.

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Xiaoling Wang