Abstract: An object recognition device includes a recognition unit, a recognition reliability calculation unit, and a combining unit. A recognition unit recognizes an object by a plurality of functions, based on information which is obtained by measuring an object by a plurality of measurement devices. A recognition reliability calculation unit calculates recognition reliability of recognition results that are obtained by recognizing an object by a recognition unit, for each function. A combining unit combines recognition reliability of the object and recognition results, detects a specified object, and outputs detection results of the specified object.

Abstract: An image recognition apparatus 100 includes a gradient feature computation unit 120 configured to calculate, from an image divided into a plurality of blocks, gradient feature values for each of the plurality of blocks, a combination pattern storage unit 160 configured to store a plurality of combination patterns of the gradient feature values, and a co-occurrence feature computation unit 131 configured to calculate a co-occurrence feature value in a plurality of blocks for each of the plurality of combination patterns. Further, image recognition apparatus 100 includes an arithmetic computation unit 132 configured to calculate an addition value by adding the co-occurrence feature value calculated for each of the plurality of blocks for each of the plurality of combination patterns, a statistical data generation unit 140 configured to generate statistical data from the addition value.

Abstract: In a video surveillance system, confirming videos from plurality of cameras causes a heavy burden on surveillance officers, and it is difficult to select a suitable video for observation. A video surveillance system includes a plurality of cameras which pick up images in a surveillance area, and a recognition unit which detects an object from videos acquired by the plurality of cameras. In the case where an object is detected in a surveillance area where images are picked up duplicately by the plurality of cameras, the recognition unit acquires a recognition result that is a feature quantity of the object for each camera. A display selection unit is, provided which, on the basis of the recognition result and a degree of priority of the recognition result, prioritizes the video from each of the cameras according to the degree of priority.

Abstract: To provide a calibration device of a camera, a camera system, and a calibration method of a camera which can achieve simplification of a calibration operation and improvement of accuracy of the calibration. A calibration device 2 includes a database 30, an instruction section 25, a correction section, and an evaluation section 24. Process data in accordance with a specification of a camera 11A is stored in the database 30. The instruction section 25 outputs an operation instruction to a display screen 50A based on the process data. The evaluation section 24 evaluates a correction image which is corrected by the correction section.

Abstract: In a calibration device, entry work of coordinate information on a real space is not required. An imaging system is configured to include an image acquisition unit which acquires an image from an imaging device, an object extraction unit which extracts a plurality of objects from the image, a characteristic information addition unit which adds geometry information that indicates geometric relationships among the plurality of objects to each set of objects as characteristic information, a camera parameter estimation unit which obtains image coordinates of the objects in accordance with the characteristic information to estimate camera parameters based on the characteristic information and the image coordinates, and a camera parameter output unit which outputs the camera parameters.

Abstract: To provide a calibration device of a camera, a camera system, and a calibration method of a camera which can achieve simplification of a calibration operation and improvement of accuracy of the calibration. A calibration device 2 includes a database 30, an instruction section 25, a correction section, and an evaluation section 24. Process data in accordance with a specification of a camera 11A is stored in the database 30. The instruction section 25 outputs an operation instruction to a display screen 50A based on the process data. The evaluation section 24 evaluates a correction image which is corrected by the correction section.

Abstract: An object detecting device includes an image acquiring unit which acquires an image from a camera, a scanning interval calculating unit which calculates a scanning interval when a scanning window is scanned on the image based on a size on the image of a detection object that is detected by the detecting window, a scanning unit which scans on the image using the scanning interval that is calculated by the scanning interval calculating unit, and a detecting unit which determines whether the detection object is present within the scanned detecting window.

Abstract: In a video surveillance system, confirming videos from plurality of cameras causes a heavy burden on surveillance officers, and it is difficult to select a suitable video for observation. A video surveillance system includes a plurality of cameras which pick up images in a surveillance area, and a recognition unit which detects an object from videos acquired by the plurality of cameras. In the case where an object is detected in a surveillance area where images are picked up duplicately by the plurality of cameras, the recognition unit acquires a recognition result that is a feature quantity of the object for each camera. A display selection unit is, provided which, on the basis of the recognition result and a degree of priority of the recognition result, prioritizes the video from each of the cameras according to the degree of priority.

Abstract: A camera surveillance system having a camera malfunction function includes an entire feature extraction unit to extract each entire feature from an input image and a reference image; a block feature extraction unit to extract block features being features of each block from images after the block division of the input image and the reference image divided into blocks by a block division unit; and a malfunction determination unit to calculate a first variation between the entire features of the reference image and the entire features of the input image, and a second variation between the block features of the reference image and the block features of the input image, to determine a camera malfunction by using a threshold, and output information indicating a type of the camera malfunction for each block.

Abstract: The object of the invention is to provide a supervising system for image to detect a scheme at high accuracy. The supervising system for image is provided with a first portion for detecting change of time detecting the change of time in amount of feature of an image taken pictures by a image forming device, a second portion for detecting change of time in the illuminance detected by an illuminance sensor, and a scheme judging portion detecting a scheme against the image forming device in accordance with the change of time in amount of feature and the change of time in the illuminance as detected.

Abstract: A device which can support a determination of a camera layout by automatically preparing the camera layout that satisfies a customer request based on the customer request including a surveillance layout. Specifically, a need table that is a data set of a plurality of arrangement candidate cameras satisfying the customer request is prepared from the customer request including the surveillance layout. An arrangement of the plurality of the arrangement candidate cameras on a map is calculated based on the need table using a clustering method and a temporary layout of cameras is prepared. Then, an arrangement layout of the cameras in the surveillance layout is determined based on the temporary layout.

Abstract: A video monitoring system, comprises a camera, and a monitor apparatus, to which video data from the camera is transmitted, wherein the camera comprises a video obtaining unit for obtaining a signal from an image pickup device, a camera image recognizer unit for executing video processing upon an input video obtained from the video obtaining unit, an encoding unit for executing an encoding process upon basis of a result of the processing within the camera image recognizer unit, thereby producing the video data, and wherein the monitor apparatus comprises a decoding unit for decoding the video data, and an image recognizer unit for selecting a decoding means of the decoding unit, upon basis of the result of processing of the camera image recognizer unit.

Abstract: An object detecting device includes an image acquiring unit which acquires an image from a camera, a scanning interval calculating unit which calculates a scanning interval when a scanning window is scanned on the image based on a size on the image of a detection object that is detected by the detecting window, a scanning unit which scans on the image using the scanning interval that is calculated by the scanning interval calculating unit, and a detecting unit which determines whether the detection object is present within the scanned detecting window.

Abstract: Recognition rate performance is prevented from dropping in executing image recognition processing on a moving object passing a surveillance area.

Abstract: This is a video image monitoring system which can effectively detect a mobile object appearing in a captured video image even if a background image and other camera condition change continuously. The video image monitoring system comprises: a video-image-capturing section 100 for putting out image data based on a video image signal obtained by using a camera 10; a mobile-object-candidate-area-detecting section 101 for extracting a candidate area of a mobile object from the image data; and a mobile-object-detecting section 102 for determining whether the candidate area is the mobile object. The mobile-object-candidate-area-detecting section 101 quantizes a brightness gradient direction of the image data, and calculates a spatio-temporal histogram which represents the frequency of a direction code appearing in a predetermined spatio-temporal space. After that, the mobile-object-candidate-area-detecting section 101 calculates a statistical spatio-temporal space evaluation value of the spatio-temporal histogram.

Abstract: A background generating method of low process cost for use in detecting a moving object based on subtraction process performed between an input image and a base image, and an apparatus with the function of detecting a moving object using its background. The apparatus consists of a feature vector extractor for calculating feature vectors from the input image and an average processor capable of obtaining an average from the calculated feature vectors, diminishing noise occurring for a short time and the influence by the moving object, and forming images that follows the illumination change due to changes in the imaging environment. The images generated by the average processor are accumulated for a predetermined number of frames and the accumulated images are statistically processed by a statistical processor.

Abstract: An image monitoring system including: an image data acquisition unit for taking in video signals from a camera to acquire image data; and an image recognition unit for carrying out image recognition processing using an inputted image obtained from the image data acquisition unit, wherein the image recognition unit includes: a reference image registration means for registering a reference image selected from among the inputted images; a motion detection means for acquiring motion detection information from the inputted image; an image blur detection means for detecting image blur by comparison of the reference image with the inputted image for edge strength; a similarity computation means for computing a similarity between the reference image and the inputted image; and a camera anomaly detection unit for determining any anomaly in the camera from the motion detection information, the image blur and the similarity, wherein the comparison for edge strength and the computation for the similarity are carried out

Abstract: A video surveillance equipment for detecting a change of an object in a monitoring area based on input images captured by an image capturing device, the equipment comprising: an area detection apparatus for detecting a second image area being stationary for a predetermined time in a first image area which is an area differing between a reference image used as a reference in image processing and the input images; a memory apparatus for storing image of the detected second image area; and an image comparison apparatus for performing comparison processing a plurality of times between the stored image and image in the second image area included in the input images.

Abstract: A failure information system that transmits various kinds of failure information of a vehicle to an outside diagnosis service center is disclosed. The failure information system includes a signal receiving unit that receives a signal indicating a failure of a vehicle-mounted system, a vehicle-run judging unit that judges that the vehicle is running, a run-distance calculation unit that calculates a run-distance of the vehicle since the signal indicating a failure is received, a reliability judging unit that judges that the signal indicating a failure is reliable if the signal receiving unit continuously receives the signal indicating a failure until the run-distance exceeds a preset distance level, and an over-vehicle communication unit that transmits the failure information that includes the signal indicating a failure when the reliability judging means judges that the signal indicating a failure is reliable.

Abstract: Behavior authority may be changed depending on a behavior performed by a person. Therefore, it is necessary to change the judgment criteria whether the behavior is anomalous or normal, in association with the changed behavior authority. Herein, an anomaly detection apparatus is provided, which calculates the behavior authority information of which judgment criteria of the anomalous and normal behaviors are changed corresponding to the behavior performed by the person, detects whether the behavior shown by the person is anomalous or not, and issues an alarm when the anomalous behavior is detected.