Sony Semiconductor Solutions Corporation

Sony Group Corporation

Norimitsu Okiyama

Hiroshi Arai

Yuji Matsui

Takeshi Masuura

Kenichiro Nishi

Satoshi Takashima

Yuriko Ohtsuka

Hiroaki Takahashi

Hiroyuki Kasahara

Yumi Nagaoka

A signal processing device according to the present technology includes a feature quantity extraction unit including a neural network and trained to extract a feature quantity for a specific event with respect to an input signal from a sensor, and a correction unit that performs correction of the input signal on the basis of the feature quantity extracted by the feature quantity extraction unit.

Signal processing device and signal processing method for correcting input signal from sensor

A signal processing device includes an approximate curved surface conversion unit that includes a first stacked autoencoder pretrained on the basis of learning input data constituted by coordinate data acquired for each of multiple elements of an object, and that obtains approximate curved surface data indicating an approximate curved surface of the object in an intermediate layer of the first stacked autoencoder, on the basis of input data constituted by the coordinate data acquired for each of the elements, and a geometric modulation processing unit that includes a second stacked autoencoder having learned by machine learning on the basis of learning input data constituted by the approximate curved surface data and on the basis of training data constituted by a result obtained by coordinate conversion for each of the elements in a geometric modulation process performed for the object, and performs the geometric modulation process.

Signal processing device and signal processing method

A signal processing device according to the present technology includes a stacked auto encoder that processes an input signal from a sensor, a control line associated learner including a neural network and subjected to control line associated learning for performing learning by associating different event aspects related to a specific event with values of different control lines with a feature quantity obtained in an intermediate layer of the stacked auto encoder after pretraining as an input, and a refactorer that obtains a difference between a first output that is an output of the control line associated learner when a first value is given to the control line, and a second output that is an output of the control line associated learner when a second value different from the first value is given to the control line.

Signal processing device, signal processing method, and parameter search method

Posture information corresponding to a line of an input image is calculated. Then, a first virtual line, which is a line in a line direction of the input image for which the posture information calculated is common, is rotated according to the posture information to obtain a second virtual line on the output image. For each pixel of the output image, a corresponding second virtual line is calculated, and posture information is obtained on the basis of the corresponding second virtual line. Then, for coordinates of each pixel of the output image, the reference coordinates on the input image corresponding to the pixel coordinates is calculated using the associated posture information. By cutting out the output image from the input image on the basis of the reference pixel, highly accurate distortion correction can be realized even in a case where the camera posture differs depending on the line.

Signal processing device, imaging device, and signal processing method

The present disclosure relates to information processing apparatus and method configured so that more information can be obtained without the need for a frame memory. Scan of a point light source or a line light source configured to project a pattern image on an object is performed, and exposure and reading by line scan for capturing an image of the object is performed multiple times during a single cycle of the scan as projection of the pattern image. The present disclosure is, for example, applicable to an information processing apparatus, an image processing apparatus, an image projection apparatus, a control apparatus, a projection image capturing system, an information processing method, a program, or the like.

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Kanagawa, Japan

Norimitsu Okiyama