Mitsubishi Electric Corporation

Yosuke Ishiwatari

Masahiko Tanimoto

Masahiro Abukawa

Hironobu Abe

Koichi Takeuchi

Hideaki Maehara

Takehiko Hanada

Haruo Nakata

A driving monitoring device () decides an applicable collision pattern that applies to a collision pattern of a case where a vehicle () collides with a mobile object, based on a velocity vector of the vehicle, a velocity vector of the mobile object, and so on. Subsequently, the driving monitoring device calculates a time until collision, which is a time taken until the vehicle collides with the mobile object, in the applicable collision pattern. Then, the driving monitoring device calculates a danger level of an accident in which the vehicle collides with the mobile object, based on the applicable collision pattern and the time until collision.

Driving monitoring device and computer readable medium

In a data synchronization device (), a first estimation unit () estimates as a first data range, a data range in which a vehicle is turning right or left, in moving image data (). A second estimation unit () estimates as a second data range, a data range in which the vehicle is turning right or left, in acceleration data (). A synchronization unit () performs a time-synchronization between the moving image data () and the acceleration data () based on a time range corresponding to the first data range estimated by the first estimation unit () and a time range corresponding to the second data range estimated by the second estimation unit ().

Data synchronization device, data synchronization method, and computer readable medium

A blind spot identification unit () identifies a plurality of obstacles causing a blind spot in an area around a vehicle. An individual calculation part () calculates, as an individual probability, a probability of occurrence of a traffic accident at a target position with respect to the position of a target object which is each of the obstacles identified by the blind spot identification unit (). A combined calculation part () calculates, as a combined probability, a probability of occurrence of a traffic accident at the target position with respect to each of the plurality of obstacles from the individual probability calculated by the individual calculation part ().

Accident probability calculator, accident probability calculation method, and non-transitory computer-readable medium storing accident probability calculation program

It is an object to obtain a high-resolution image generation apparatus that can generate a high-quality image by sorting out good portions from faulty portions in optical flow. The present invention includes: a hard disk that stores multi-viewpoint image information and parameter information of a base image and a plurality of reference images; an optical flow computation unit that extracts a plurality of pairs of the base image and a reference image, the plurality of pairs each including a different reference image, and computes optical flow for each pair; a depth information computation unit that computes depth information which indicates depth of each pixel of the base image for each pair, based on optical flow and the parameter information; and an optical flow sorting unit that determines whether or not each piece of pixel-based correspondence information included in the optical flow of each pair is to be used for improving a resolution of the base image, based on two pieces of the depth information.

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Tokyo, Japan

Yosuke Ishiwatari