Abstract: A vital sign detection device includes: a sensor signal acquiring unit to acquire a sensor signal representing a sensing result of a biosensor to sense a vital sign of a measurement subject; a spectrum calculating unit to calculate a frequency spectrum of the sensor signal; a frequency component identifying unit to identify one or more frequency components which may represent vital signs of the measurement subject, in a plurality of frequency components included in the frequency spectrum calculated; a noise band identifying unit to identify a noise band which is a noise-containing frequency band, from a noise signal representing an observation result of a noise observer to observe noise which may be mixed in the sensor signal representing the sensing result of the biosensor; and a noise removing unit to remove a frequency component which is included in the noise band identified, in the one or more frequency components identified.

Abstract: Provided are a vehicle outside information acquiring unit to acquire vehicle outside information, a face information acquiring unit to acquire face information, a biological information acquiring unit to acquire biological information, a vehicle information acquiring unit to acquire vehicle information, a vehicle outside information feature amount extracting unit to extract a vehicle outside information feature amount on the basis of the vehicle outside information, a face information feature amount extracting unit to extract a face information feature amount in accordance with the vehicle outside information feature amount, a biological information feature amount extracting unit to extract a biological information feature amount in accordance with the vehicle outside information feature amount, a vehicle information feature amount extracting unit to extract a vehicle information feature amount in accordance with the vehicle outside information feature amount, and a cognitive function estimation unit to estim

Abstract: Provided are a vehicle outside information acquiring unit to acquire vehicle outside information, a face information acquiring unit to acquire face information, a biological information acquiring unit to acquire biological information, a vehicle information acquiring unit to acquire vehicle information, a vehicle outside information feature amount extracting unit to extract a vehicle outside information feature amount on the basis of the vehicle outside information, a face information feature amount extracting unit to extract a face information feature amount in accordance with the vehicle outside information feature amount, a biological information feature amount extracting unit to extract a biological information feature amount in accordance with the vehicle outside information feature amount, a vehicle information feature amount extracting unit to extract a vehicle information feature amount in accordance with the vehicle outside information feature amount, and a cognitive function estimation unit to estim

Abstract: A facial information detecting unit detects facial information related to facial features of a driver of a vehicle. A physical information detecting unit detects physical information related to physical features of the driver. A driving capability estimating unit estimates a driving capability of the driver on the basis of the facial information and the physical information. A facial expression estimating unit estimates the facial expression of the driver on the basis of the facial information. An emotion estimating unit estimates the emotion of the driver represented by the degree of comfort and the degree of activeness on the basis of temporal changes in the driving capability of the driver and the facial expression of the driver.

Abstract: A facial information detecting unit detects facial information related to facial features of a driver of a vehicle. A physical information detecting unit detects physical information related to physical features of the driver. A driving capability estimating unit estimates a driving capability of the driver on the basis of the facial information and the physical information. A facial expression estimating unit estimates the facial expression of the driver on the basis of the facial information. An emotion estimating unit estimates the emotion of the driver represented by the degree of comfort and the degree of activeness on the basis of temporal changes in the driving capability of the driver and the facial expression of the driver.

Abstract: Provided is a line-of-sight detection apparatus that outputs reliability of an estimation result of a line of sight when an eye to be a line-of-sight detection target is switched. The line-of-sight detection apparatus includes: an estimation target selection unit configured to select an eye of a line-of-sight detection target person as one of switchable line-of-sight detection modes; a line-of-sight estimation unit configured to estimate a line of sight of the line-of-sight detection target person in the line-of-sight detection mode; a reliability determination unit configured to determine, based on a first line of sight before the mode is switched and a second line of sight after the mode is switched, reliability of the second line of sight; and a line-of-sight direction output unit configured to output information on the second line of sight and the reliability of the second line of sight.

Abstract: An abnormality detection device includes processing circuitry configured to calculate an index value indicating a sum of edge strengths in a second image that is an image captured by a camera for capturing a vehicle compartment at timing before a user enters a vehicle, calculate a differential value between an index value indicating a sum of edge strengths in a reference image, which is an image captured by the camera under an imaging condition equivalent to an imaging condition of the second image before the second image is captured, and the calculated index value, determine whether the differential value is equal to or greater than a threshold value, and execute control to output a warning in a case where it is determined that the differential value is equal to or greater than the threshold value.

Abstract: An abnormality detection device includes processing circuitry configured to calculate an index value indicating a sum of edge strengths in a second image that is an image captured by a camera for capturing a vehicle compartment at timing before a user enters a vehicle, calculate a differential value between an index value indicating a sum of edge strengths in a reference image, which is an image captured by the camera under an imaging condition equivalent to an imaging condition of the second image before the second image is captured, and the calculated index value, determine whether the differential value is equal to or greater than a threshold value, and execute control to output a warning in a case where it is determined that the differential value is equal to or greater than the threshold value.