Abstract: The present disclosure relates to an information processing device, an information processing method, and a program for improving object recognition accuracy. A feature amount obtained by a point cloud that is a dense detection point of LiDAR or the like and a feature amount of a sparse detection point of a millimeter wave radar or the like within a predetermined distance are grouped and integrated with reference to the position of the feature amount of the dense detection point, the point cloud is restored using an integrated feature amount of the dense detection point, and object recognition processing such as semantic segmentation is performed. The present disclosure can be applied to a mobile body.

Abstract: An imaging apparatus includes: an imaging unit that has a pixel region in which a plurality of pixels is arranged and that reads and outputs a pixel signal from the pixels included in the pixel region; a unit-of-readout controller that controls a unit of readout set as a part of the pixel region: a recognition unit that has learned training data for each of units of readout; a first output unit that outputs a recognition result of recognition performed by the recognition unit for each of the units of readout; a second output unit that outputs the pixel signal to a subsequent stage; and a trigger generator that generates a trigger signal for controlling a first timing at which the first output unit outputs the recognition result and a second timing at which the second output unit outputs the pixel signal.

Abstract: An information processing apparatus according to an embodiment includes: a conversion part that converts a first dataset or a first recognizer for performing a recognition process based on a first signal read from a first sensor into a second dataset or a second recognizer for performing a recognition process based on a second signal read from a second sensor. The first sensor performs reading in a first reading unit and the second sensor performs reading in a second reading unit different from the first reading unit.

Abstract: An information processing apparatus according to an embodiment includes a generation part (301) that generates, based on a dataset (300, 303) or a first recognizer (310) for training the first recognizer that performs a recognition process based on a first signal read from a first sensor, control information (313) for controlling a recognition process by a second recognizer (312) that performs the recognition process based on a second signal read from a second sensor having a reading unit different from the first sensor.

Abstract: An information processing apparatus includes a conversion part that trains a second recognizer based on an output of a first recognizer that performs a recognition process based on a first signal read from a first sensor. The second recognizer performs the recognition process based on a second signal read from a second sensor having a characteristic different from the first sensor.

Abstract: An information processing apparatus according to an embodiment includes a conversion part (311) that converts, based on an output of a first recognizer (310) that performs a recognition process based on a first signal read from a first sensor, a processing parameter related to a recognition process of a second recognizer (312) that performs the recognition process based on a second signal read from a second sensor having a characteristic different from a characteristic of the first sensor. The conversion part converts the processing parameter so as to approximate an output of the second recognizer to an output of the first recognizer.

Abstract: An information processing apparatus includes a conversion part that converts a first recognizer or a first dataset for performing a recognition process based on a first signal read from a first sensor having a first pixel characteristic or a first signal characteristic into a second recognizer or a second dataset for performing a recognition process based on a second pixel characteristic different from the first pixel characteristic or a second signal characteristic different from the first signal characteristic.

Abstract: An information processing apparatus according to an embodiment includes a generation part that generates a signal corresponding to a first signal read from a first sensor. The signal is generated based on a second signal read from a second sensor different from the first sensor in at least one of a reading unit, a pixel characteristic, and a signal characteristic.

Abstract: An imaging apparatus includes: an imaging unit that has a pixel region in which a plurality of pixels is arranged and that reads and outputs a pixel signal from the pixels included in the pixel region; a unit-of-readout controller that controls a unit of readout set as a part of the pixel region: a recognition unit that has learned training data for each of units of readout; a first output unit that outputs a recognition result of recognition performed by the recognition unit for each of the units of readout; a second output unit that outputs the pixel signal to a subsequent stage; and a trigger generator that generates a trigger signal for controlling a first timing at which the first output unit outputs the recognition result and a second timing at which the second output unit outputs the pixel signal.

Abstract: An imaging apparatus includes: an imaging unit that has a pixel region in which a plurality of pixels is arranged and reads and outputs a pixel signal from the pixels included in the pixel region; a unit-of-readout controller that controls a unit of readout set as a part of the pixel region; a first unit-of-readout setting unit that sets a first unit of readout that is used for reading out the pixel signal from the pixel region for a recognition process that has learned training data for each of the units of readout; a second unit-of-readout setting unit that sets a second unit of readout that is used for reading out the pixel signal from the pixel region so as to output the pixel signal to a subsequent stage; and a mediation unit that performs mediation between the first unit of readout and the second unit of readout.

Abstract: An imaging apparatus according to an embodiment includes: an imaging unit having a pixel region in which a plurality of pixels is arranged; a readout controller that controls readout of pixel signals from pixels included in the pixel region; a first unit-of-readout setting unit that sets a unit of readout as a part of the pixel region, for which the readout controller performs readout of the pixel signal; an image output unit that outputs a first image based on the pixel signal read out from the unit of readout to a subsequent stage; a second unit-of-readout controller that controls the unit of readout in which the readout controller performs readout of the pixel signal; and a recognition unit that learns training data for each of the units of readout, performs a recognition process on the pixel signal for each of the units of readout, and outputs a recognition result.

Abstract: The present disclosure relates to an information processing device, an information processing method, and a program for improving object recognition accuracy. A feature amount calculation unit of a user's car calculates a feature amount for an object recognition result in stages in each of a plurality of hierarchies, an acquisition unit acquires a feature amount for an object recognition result calculated by a feature amount calculation unit of another car, and a recognition unit performs the object recognition on the basis of the feature amount calculated by the user's car and the acquired feature amount calculated by the another car. The present disclosure can be applied to a mobile body.

Abstract: The present disclosure relates to an information processing device, an information processing method, and a program for improving object recognition accuracy. A feature amount calculation unit of a user's car calculates a feature amount for an object recognition result in stages in each of a plurality of hierarchies, an acquisition unit acquires a feature amount for an object recognition result calculated by a feature amount calculation unit of another car, and a recognition unit performs the object recognition on the basis of the feature amount calculated by the user's car and the acquired feature amount calculated by the another car. The present disclosure can be applied to a mobile body.

Abstract: An information processing system includes: a user information accumulation unit that accumulates information regarding a user on a basis of an action of the user; a specifying unit that specifies information corresponding to sensitive information among the accumulated information as corresponding to the sensitive information; and a disclosure control unit that controls a disclosure mode of the information corresponding to the sensitive information in a case where the information corresponding to the sensitive information is disclosed to a third party other than the user.

Abstract: An imaging section images a passenger in a moving body. A boarding state detection section detects a boarding state of the passenger on the basis of a captured image. An allowable acceleration setting section sets, for each passenger, individual allowable acceleration on the basis of the boarding state of the passenger, for example, the lateral spacing between the feet of the passenger, the arrangement angle of the feet with respect to the moving direction of the moving body, and the like. Further, integration is performed on the individual allowable acceleration determined for the respective passengers in the moving body, and the acceleration that is allowable for the moving body is set The according to the boarding state of each passenger. Thus, the moving body is prevented from moving at acceleration at which the passengers may be endangered.

Abstract: The present technology relates to an information processing system, an information processing method, and a program that make it possible to determine execution of learning, without relying on external instruction inputs. The information processing system determines an action on the basis of environmental information and a learning model obtained through learning based on an evaluation function for evaluating an action.

Abstract: The present technology relates to an information processing system, an information processing method, and a program that are capable of facilitating the understanding of an explanation regarding AI processing. The information processing system includes an evaluation portion that evaluates multiple choices according to two or more evaluation criteria based on parameters obtained during a process or a result of machine learning, and an explanation portion that generates explanatory text regarding each of the choices by using a phrase associated with a corresponding one of the evaluation criteria. For example, the present technology is applicable to hardware and software performing various processes with the use of AI.

Abstract: The present disclosure relates to an information processing system, an information processing method, and an information processing device that make it possible to perform learning adaptively to changes in an external environment and circumstances. A learning section learns results of action selection made by a system in response to input information. An input information assessment section assesses a risk of the input information to the system. A first parameter calculation section calculates a first parameter representing stress on the system according to an assessed value of the input information. The learning section changes learning efficiency according to the first parameter. The technology according to the present disclosure is applicable, for example, to an information processing system that performs machine learning.

Abstract: An imaging device includes: an imaging section that has a pixel region where a plurality of pixels is arrayed, a readout unit control section that controls readout units each set as a part of the pixel region, a readout control section that controls readout of pixel signals from the pixels included in the pixel region for each of the readout units set by the readout unit control section, a recognition section that has a machine learning model trained on the basis of leaning data, and a determination basis calculation section that calculates a determination basis of a recognition process performed by the recognition section. The recognition section performs the recognition process for each of the readout units. The determination basis calculation section calculates a determination basis for each of the readout units.

Abstract: Information processing is implemented which analyzes the cause of the result of recognition using a machine learning model. An information processing apparatus includes: a recognition processing section configured to perform object recognition processing on sensor information from a sensor section by use of a trained machine learning model; a causal analysis section configured to analyze the cause of a result of recognition by the recognition processing section on the basis of the sensor information from the sensor section and the result of recognition by the reception processing section; and a control section configured to control an output of the sensor section. The sensor section is an image sensor. The causal analysis section determines the cause of a drop in characteristic of recognition by the recognition processing section on the basis of low-resolution high-bit-length image data for causal analysis.