Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A signal processing apparatus includes: a data input unit to which image data is input; an output unit configured to output an output value based on the data input to the data input unit; an expectation feedback calculator configured to calculate a difference between an expectation based on the input data and the output value; and a Bayesian estimator to which information on the difference and information based on the image data are input and which is configured to perform machine learning in order to approximate the output value to the expectation based on the input information and to search for an optimum configuration.

Abstract: Provided are an information collection system, an electronic shelf label, an electronic POP advertising, and a character information display device that allow information with higher accuracy to be collected. An information collection device that collects information associated with a customer or a product is included for each product type. Alternatively, an information processing device that supplies information associated with a product and an information display terminal that displays information associated with a product supplied from the information processing device are included.

Abstract: The present technology relates to an information collection system, an electronic shelf label, an electronic POP advertising, and a character information display device that allow information with higher accuracy to be collected. An information collection device that collects information associated with a customer or a product is included for each product type. Alternatively, an information processing device that supplies information associated with a product and an information display terminal that displays information associated with a product supplied from the information processing device are included. The present disclosure can be applied, for example, to an electronic shelf label, an image pickup device, a communication device, an information processing device, electronic equipment, a computer, a storage medium, a system, and the like.

Abstract: The present technology relates to a monitoring system, a monitoring sensor apparatus, a monitoring method and a program that make it possible to detect a failure of IR illumination on the basis of picked up images.

Abstract: The present technology relates to an information collection system, an electronic shelf label, an electronic POP advertising, and a character information display device that allow information with higher accuracy to be collected. An information collection device that collects information associated with a customer or a product is included for each product type. Alternatively, an information processing device that supplies information associated with a product and an information display terminal that displays information associated with a product supplied from the information processing device are included. The present disclosure can be applied, for example, to an electronic shelf label, an image pickup device, a communication device, an information processing device, electronic equipment, a computer, a program, a storage medium, a system, and the like.

Abstract: To accurately determine whether there is a sharp change in a frame. Provided is an image processing device including: a histogram generating unit configured to generate a previous histogram showing a distribution of pixel values in a previous frame that is generated before a predetermined frame and a current histogram showing a distribution of pixel values in the predetermined frame; a normalizing unit configured to perform normalization to match variations of the pixel values of the previous histogram and the current histogram; and a similarity determining unit configured to acquire a degree of similarity of shapes of the previous histogram and the current histogram after the normalization and determine whether the degree of similarity is greater than a predetermined similarity determining threshold value.

Abstract: To accurately determine whether there is a sharp change in a frame. Provided is an image processing device including: a histogram generating unit configured to generate a previous histogram showing a distribution of pixel values in a previous frame that is generated before a predetermined frame and a current histogram showing a distribution of pixel values in the predetermined frame; a normalizing unit configured to perform normalization to match variations of the pixel values of the previous histogram and the current histogram; and a similarity determining unit configured to acquire a degree of similarity of shapes of the previous histogram and the current histogram after the normalization and determine whether the degree of similarity is greater than a predetermined similarity determining threshold value.

Abstract: An image processing device includes: an acquisition section configured to acquire image data of a captured image; a dividing section configured to divide the acquired image data into divisional regions; a characteristic-amount calculation section configured to calculate a characteristic amount of the image data in each of the divisional regions; a characteristic-amount storage section configured to update the calculated characteristic amount and store the updated characteristic amount sequentially; and a change determination section configured to perform first and second processings, the first processing being provided to calculate a change amount or an agreement amount between the characteristic amounts, the second processing being provided to calculate a difference value between the characteristic amounts, and the change determination section being configured to determine, based on processing contents of the first and second processings, whether or not the update region is a changed region.

Abstract: This technique relate to an image processing device, an image processing method, an imaging device, an electronic equipment, and a program which can provide a technique to execute a highly accurate global motion search process which is robust to a local moving subject, an illumination intensity change, and the like.

Abstract: An image processing device includes: an acquisition section configured to acquire image data of a captured image; a dividing section configured to divide the acquired image data into divisional regions; a characteristic-amount calculation section configured to calculate a characteristic amount of the image data in each of the divisional regions; a characteristic-amount storage section configured to update the calculated characteristic amount and store the updated characteristic amount sequentially; and a change determination section configured to perform first and second processings, the first processing being provided to calculate a change amount or an agreement amount between the characteristic amounts, the second processing being provided to calculate a difference value between the characteristic amounts, and the change determination section being configured to determine, based on processing contents of the first and second processings, whether or not the update region is a changed region.

Abstract: This technique relate to an image processing device, an image processing method, an imaging device, an electronic equipment, and a program which can provide a technique to execute a highly accurate global motion search process which is robust to a local moving subject, an illumination intensity change, and the like.