Abstract: A pipeline processing system which processes a pipeline connecting multiple blocks that are executable programs with ability to load a trained neural network model for inference processing comprises: a block file storage circuitry configured to store each block file configuring the pipeline; a configuration information storage circuitry configured to store pipeline configuration information which is information that defines the pipeline configuration and includes information about all blocks that make up the pipeline and information about the execution order of each block that makes up the pipeline; and a pipeline processing control circuitry configured to load and execute each of the blocks included in the pipeline using data input from programs outside the pipeline according to the pipeline configuration information, and return the execution results of the pipeline processing to the external programs.

Abstract: A dataset generation system has a camera classification circuitry configured to classify plural cameras into plural groups, an input device for a user to set a selecting criterion of a captured image, a first captured image collection circuitry configured to collect captured images which are captured by at least one camera in each group classified by the camera classification circuitry, and which meet the selecting criterion set by a user using the input device, an inference circuitry configured to perform inference processing on each of the captured images collected by the first captured image collection circuitry and a dataset evaluation circuitry configured to evaluate whether or not a dataset consisting of the captured images collected by the first captured image collection circuitry is suitable for a training dataset of a neural network model for a predetermined inference process, based on the result of the inference processing by the inference circuitry.

Abstract: A signage control system comprises: a primary estimation circuitry to use signage-side images and surveillance-side images to estimate a person feature, attributes and behavior of each person captured in these frame images; a storage device to associate and store results of estimations of the person feature, the attributes and the behavior of each specific person; an estimation result linkage circuitry to use the person feature stored in the storage device to link the results of estimations based on the frame images from multiple ones of the cameras for the same person so as to generate a group of estimation results for each person; and a content change circuitry to change a content displayed on the signage to another based on the attributes of each person expected to be in a position where such person can visually recognize the content on the signage, and based on preceding behavior of such person.

Abstract: A group-specific model generation system includes: a captured image collection circuitry configured to collect a captured image from each of cameras; an image feature extraction circuitry configured to extract a feature from each of the captured images; an image clustering circuitry configured to group the captured image based on the feature of each of the captured images; a camera classification circuitry configured to classify cameras into groups, based on a result of the grouping of the captured images; and a group-specific model generation circuitry configured to generate a group-specific learned neural network model suitable for captured images taken by the cameras in the each of the groups.

Abstract: An attribute recognition system has a person face detection circuitry to detect a suitable person or face for recognition of at least one attribute from persons or faces captured in frame images input from at least one camera to capture a given capture area, an identification information assignment circuitry to identify the persons or faces captured in the frame images having been subjected to the detection by the person face detection circuitry so as to assign an identification information to each identified person or face, and an attribute recognition circuitry to recognize the attribute of a person or face assigned with the identification information, only if the person or face is yet without being subjected to recognition of the attribute, and at the same time if the person or face has been detected by the person face detection circuitry as a suitable person or face for the recognition of the attribute.

Abstract: An image analysis device has: an image analysis circuitry to analyze images input from each of cameras using instances of an image analysis program including a learned neural network model for object detection and learned neural network models for object recognition; inference processors to perform inference processes in the learned neural network model for object detection and each learned neural network model for object recognition; and a processor assignment circuitry to assign, from the inference processors, inference processors to be used for the inference process in the learned neural network model for object detection and the inference process in each learned neural network model for object recognition, based on inference time and frequency of use required for the inference process in each of the learned neural network models for object detection and object recognition included in each instance of the image analysis program.

Abstract: A signage control system comprises: a primary estimation circuitry to use signage-side images and surveillance-side images to estimate a person feature, attributes and behavior of each person captured in these frame images; a storage device to associate and store results of estimations of the person feature, the attributes and the behavior of each specific person; an estimation result linkage circuitry to use the person feature stored in the storage device to link the results of estimations based on the frame images from multiple ones of the cameras for the same person so as to generate a group of estimation results for each person; and a content change circuitry to change a content displayed on the signage to another based on the attributes of each person expected to be in a position where such person can visually recognize the content on the signage, and based on preceding behavior of such person.

Abstract: An attribute recognition system has a person face detection circuitry to detect a suitable person or face for recognition of at least one attribute from persons or faces captured in frame images input from at least one camera to capture a given capture area, an identification information assignment circuitry to identify the persons or faces captured in the frame images having been subjected to the detection by the person face detection circuitry so as to assign an identification information to each identified person or face, and an attribute recognition circuitry to recognize the attribute of a person or face assigned with the identification information, only if the person or face is yet without being subjected to recognition of the attribute, and at the same time if the person or face has been detected by the person face detection circuitry as a suitable person or face for the recognition of the attribute.

Abstract: An image analysis device has: an image analysis circuitry to analyze images input from each of cameras using instances of an image analysis program including a learned neural network model for object detection and learned neural network models for object recognition; inference processors to perform inference processes in the learned neural network model for object detection and each learned neural network model for object recognition; and a processor assignment circuitry to assign, from the inference processors, inference processors to be used for the inference process in the learned neural network model for object detection and the inference process in each learned neural network model for object recognition, based on inference time and frequency of use required for the inference process in each of the learned neural network models for object detection and object recognition included in each instance of the image analysis program.