Nec Corporation

Nec C Orporation

Hiroo Ikeda

Ryoma Oami

Takuya Ogawa

Ryo Kawai

Hiroshi Yamada

Junko Nakagawa

Yusuke Takahashi

Yukie Ebiyama

Katsuhiko Takahashi

Kosuke Yoshimi

Hiroyoshi Miyano

Kazuya Koyama

Yuusuke Konishi

Yusuke Konishi

Muneaki Onozato

Satoshi Terasawa

Yuji Shinozaki

Hiroo Harada

An object position estimation device () is provided with: a feature extraction unit () including a first feature extraction unit () which generates a first feature map by subjecting a target image to a convolution computation process, and a second feature extraction unit () which generates a second feature map by also subjecting the first feature map to the convolution computation process; and a likelihood map estimation unit () including a first position likelihood estimation unit () which, by using the first feature map, estimates a first likelihood map indicating the probability that first objects having a first size are present in the target image, and a second position likelihood estimation unit () which, by using the second feature map, estimates a second likelihood map indicating the probability that second objects having a second size, which is greater than the first size, are present in the target image.

Object position estimation device, object position estimation method, and recording medium

In order to acquire recognition environment information impacting the recognition accuracy of a recognition engine, an information processing devicecomprises a detection unitand an environment acquisition unit. The detection unitdetects a marker, which has been disposed within a recognition target zone for the purpose of acquiring information, from an image captured by means of an imaging device which captures images of objects located within the recognition target zone. The environment acquisition unitacquires the recognition environment information based on image information of the detected marker. The recognition environment information is information representing the way in which a recognition target object is reproduced in an image captured by the imaging device when said imaging device captures an image of the recognition target object located within the recognition target zone.

Information processing device and recognition support method

A queue analysis apparatus () estimates a position and an orientation of each object () included in a target image (). The target image () is generated by a camera () that captures the object (). The queue analysis apparatus () generates a queue line () that expresses, by a linear shape, a queue included in a queue region () being a region representing a queue in the target image (), based on a position and an orientation being estimated for each object () included in the queue region ().

Queue analysis apparatus, control method, and non-transitory computer-readable medium

A flow-rate information output apparatus () computes the number of objects () passing through a surveillance location () included in a target image () with respect to each of a plurality of surveillance directions (). The flow-rate information output apparatus () generates, with respect to one or more surveillance directions (), a flow rate mark () relevant to the number of objects () passing through the surveillance location () toward the surveillance direction (). The flow-rate information output apparatus () generates a result image () by superimposing the flow rate mark () on an image including the surveillance location ().

Flow-rate information output apparatus, control method, and non-transitory computer-readable medium

An image processing device () comprises an input unit () and a presentation unit (). The input unit () accepts an input of an operation for movement, on a captured image captured by a camera, of a first image which is superimposed on the captured image on the basis of a predetermined camera parameter indicating the position and attitude of the camera and which indicates a target object having a predetermined shape and a predetermined size set in a real space. The presentation unit () presents the first image indicating the target object in a manner of view corresponding to a position on the captured image after the movement on the basis of the camera parameter.

Image processing device, image processing method, and recording medium

A guidance processing apparatus () includes an information acquisition unit () that acquires a plurality of different pieces of guidance information on the basis of states of a plurality of people within one or more images, and a control unit () that performs control of a plurality of target devices present in different spaces or time division control of a target device so as to set a plurality of different states corresponding to the plurality of pieces of guidance information.

Guidance processing apparatus and guidance method

An information processing device of the present invention includes a detection means that detects the content of an image, a determination means that determines a processing mode for the image based on the result of detection of the content of the image, and an execution means that executes processing for a captured image corresponding to the processing mode.

Information processing device

An object count estimation apparatus () includes a first feature extraction network (), a first counting network (), a second feature extraction network (), and a second counting network (). The first feature extraction network () generates a first feature map () by performing convolution processing on a target image (). The first counting network () estimates the number of target objects having a size included in a first predetermined range by performing processing on the first feature map (). The second feature extraction network () generates a second feature map () by performing convolution processing on the first feature map (). The second existence estimation network () estimates the number of target objects having a size included in a second predetermined range by performing processing on the second feature map (). A size included in the first predetermined range is smaller than a size included in the second predetermined range.

Object number estimation device, control method, and program

An image processing system, an image processing method, and a program capable of implementing an association of a person appearing in a video image through a simple operation are provided. The image processing system includes an input device which accepts input of video images captured by a plurality of video cameras, a display screen generating unit which causes a display device to display at least one video image among the video images inputted from the input device, and a tracked person registering unit which is capable of registering one or more persons appearing in the video image displayed by the display device. When a person appears in the video image displayed by the display device, the display screen generating unit selectably displays person images of one or more persons, which are associable with the person appearing in the video image and which are registered by the tracked person registering unit, in a vicinity of the video image.

Image processing system, image processing method, and program

At least one processor generates a crowd state image as an image in which a person image corresponding to a person state is synthesized with previously-prepared image at a predetermined size. The at least one processor specifies a training label for the crowd state image. The at least one processor outputs a pair of crowd state image and training label.

Training data generating device, method, and program, and crowd state recognition device, method, and program

At least one processor generates a crowd state image as an image in which a person image corresponding to a person state is synthesized with previously-prepared image at a predetermined size. The previously-prepared image is an background image that include no person. The at least one processor specifies a training label for the crowd state image. The at least one processor outputs a pair of crowd state image and training label.

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Tokyo, Japan

Hiroo Ikeda