Panasonic Intellectual Property Management Co., Ltd.

Panasonic Corporation

Panasonic Intellectual Property Corporation of America

Shinji Takenaka

Yoshiteru Mino

Kazuhiko Iwai

Junko Ueda

Mitsuko Fujita

Yuichiro Takemoto

Masashi Okada

Hideki Takahashi

Satoru Oyabu

Yasuyuki Michimoto

Kenji Tokuda

Tatsuki Hotani

An in-cabin monitoring system includes a camera which captures an image of an inside of a cabin of a vehicle, a light source which irradiates the inside of the cabin with light, and a controller which controls the camera and the light source. The light source is capable of emitting first light which is light to be emitted when checking whether a person is present using the camera and second light which is stronger than the first light. The controller captures an image of the inside of the cabin using the camera while causing the light source to emit the second light, before the person gets in the vehicle and after the person gets out of the vehicle.

In-cabin monitoring system and in-cabin detection method

An object tracking method includes: predicting a prediction distribution which is a distribution of each of prediction pose locations of first objects in a current frame by inputting pose time-sequence data to a pose predictor; estimating a set of locations of each of second objects in the current frame by inputting the current frame to a pose estimator; obtaining identification information indicating a one-to-one correspondence between the second objects and the first objects and location information of the second objects by matching the set of locations and the prediction distribution, to output the obtained identification information and location information; and updating the pose time-sequence data by adding, to the pose time-sequence data and based on the obtained identification information and location information, data which includes coordinates indicating a pose of each of the first objects and is obtained from the predicted prediction distribution.

Object tracking method and recording medium

To precisely specify lane regions that are present in an image. In a situation in which a lane specification device an imaging device, and a swimming pool are present, a processor in the lane specification device according to the present disclosure specifies lane regions that are present in an image on the basis of a pattern in which information obtained on the basis of outlines of objects in the image captured by the imaging device appears in the image. In this manner, it is possible to precisely specify the lane regions that are present in the image.

Lane specification method and lane specification device

A product monitoring device is provided that presents, to the user, information by which the user can recognize specific work items of a product management work for improving an inappropriate display state. The product monitoring device acquires a captured image of a display area, sets a state monitoring area on the captured image of the display area, acquires product detection information indicating a position of a product in the state monitoring area, based on a captured image of the state monitoring area, evaluates a display state of the product in the state monitoring area, using a plurality of evaluation indices relating to display disorder of the product, based on the product detection information, and presents information on an evaluation result to a user.

Product monitoring device, product monitoring system, and product monitoring method

A human detection and tracking apparatus prevents errors in a size of a person and a location of body parts between actual image data and a tracking result. Human frame detecting section detects, from first image data, a human frame as a region having high possibility of presence of a human, based on human feature data representing a feature of an entire human body. Body part frame location determining section determines a body part frame in the first image data, based on part feature data illustrating a feature of a body part of the human and a part frame determined as a region having high possibility of presence of a body part of the human in second image data previous to the first image data. Body part frame location correcting section corrects, based on the human frame, a location of the part frame determined in the first image data.

Human detection and tracking apparatus, human detection and tracking method, and human detection and tracking program

Disclosed is a moving object automatic tracking apparatus that includes a movement detector for detecting movement of a moving object from an image obtained in time series from an image input portion. A tracker tracks the moving object by controlling a platform of the image input portion in a direction of movement of the moving object based on a movement detection result of the movement detector. An area manager manages a registered preset position and new registration of a preset position indicating an area for executing tracking by the tracker and movement detection by the movement detector. A patrol monitor conducts monitoring while patrolling plural preset positions set and managed by the area manager, and when a position in which the moving object is tracked and lost differs from the initialized preset position, the lost position is newly added and registered as an adaptive preset position.

Growing community of inventors

Ishikawa, Japan

Shinji Takenaka