Oki Electric Industry Co., Ltd.

Makoto Masuda

Hideto Koike

Shigeru Tatsuzawa

Kagehiro Nagao

Hiroyuki Hota

Shunsuke Ichihara

Reiko Kishi

Kouhei Endou

Kenji Murakami

The present disclosure provides a surveillance device that monitors an operation section of an automated transaction device, the surveillance device including: a learning holding section that learns and holds a reference scene data set in which a reference operation is divided into a sequence of action items; a feature extraction section that extracts actual target action data from actual scene data of the sequence of action items in an operation of a user, the actual scene data obtained from an imaging section that faces and images the operation section; and a detection section that associates actual target action data with a reference scene data set along the sequence of action items, compares for each of the action items, determines an anomaly level of the operation of the user, and outputs an anomalous occurrence signal according to the anomaly level.

Surveillance device

An image processing apparatus including a region-of-interest decision unit that identifies an interest space region in which an object to be analyzed is likely to be present based on a distance image, which is shape information of an object space corresponding to a captured image to be analyzed acquired by a distance image sensor, to identify a region of interest in the captured image corresponding to the interest space region and an image analysis unit that performs different image analyses for the region of interest and other image regions.

Image processing apparatus, image processing method, program, and image processing system

A face recognition system includes: an image input section that acquires a facial image of a user; a database in which a feature value of a part of a face of a registered person is stored; a facial position detection section that detects a position of a part of a face from the facial image of the user; a feature value extraction section that extracts a feature value of the part of the face; and a recognition section that recognizes the user by comparing the feature value of the part of the face which is extracted by the feature value extraction section with the feature value of the part of the face of the registered person stored in the database, in which the user selects the part of the face from which the feature value is extracted.

Face recognition system

Growing community of inventors

Saitama, Japan

Makoto Masuda