Abstract: An information processing apparatus includes a comparison unit configured to compare an image capturing condition for a collation target object with an image capturing condition for each of a plurality of image capturing apparatuses, a selection unit configured to select an image capturing apparatus to be collated from among the plurality of image capturing apparatuses based on a result of the comparison by the comparison unit, and a collation unit configured to collate information about an object captured by the image capturing apparatus to be collated with information about the collation target object.

Abstract: An information processing apparatus includes a comparison unit configured to compare an image capturing condition for a collation target object with an image capturing condition for each of a plurality of image capturing apparatuses, a selection unit configured to select an image capturing apparatus to be collated from among the plurality of image capturing apparatuses based on a result of the comparison by the comparison unit, and a collation unit configured to collate information about an object captured by the image capturing apparatus to be collated with information about the collation target object.

Abstract: An apparatus includes an analysis unit configured to analyze a state of an environment at a time when a capturing unit captures a video image, based on a parameter for correcting the captured video image, a recognition unit configured to perform recognition processing on the captured video image, using a classifier, and a learning unit configured to learn the classifier based on a result of the analysis performed by the analysis unit and a result of the recognition performed by the recognition unit.

Abstract: An apparatus includes an analysis unit configured to analyze a state of an environment at a time when a capturing unit captures a video image, based on a parameter for correcting the captured video image, a recognition unit configured to perform recognition processing on the captured video image, using a classifier, and a learning unit configured to learn the classifier based on a result of the analysis performed by the analysis unit and a result of the recognition performed by the recognition unit.

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 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: 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: 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: 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 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 image processing apparatus, for example, a multi-camera monitoring system is provided for processing images with the intention of protecting the individuals' privacies in accordance with the type of customers in a store which is equipped with the multi-camera monitoring system, and for deleting or modifying individuals' privacy information to protect the individuals' privacies while permitting the identity of a person to be determined among a plurality of cameras. The image processing apparatus processes an image captured by an imager device to output the resulting image. A processor detects a person from an image, and an image database stores feature information on the person. The processor extracts features from the detected person and the database, processes the extracted feature amount in the stored feature information, and generates an output image based on the processed features.

Abstract: An image processing apparatus, for example, a multi-camera monitoring system is provided for processing images with the intention of protecting the individuals' privacies in accordance with the type of customers in a store which is equipped with the multi-camera monitoring system, and for deleting or modifying individuals' privacy information to protect the individuals' privacies while permitting the identity of a person to be determined among a plurality of cameras. The image processing apparatus processes an image captured by an imager device to output the resulting image. A processor detects a person from an image, and an image database stores feature information on the person. The processor extracts features from the detected person and the database, processes the extracted feature amount in the stored feature information, and generates an output image based on the processed features.

Abstract: This invention is to provide a shape measuring device and a shape measuring method that can accurately measure a cross-sectional shape or a three-dimensional shape of a sample without using matching of characteristics. A shape measuring apparatus comprises a charged particle beam apparatus comprising a processor for measuring detected charged particles signal generated from the sample. The charged particle beam is irradiated to sample at first angle to generate a first signal and second angle to generate second signal. The processor selects a parameter indicating a relation between the first signal and a height of the sample or an inclination angle of the specimen until the first signal which achieves the second signal.

Abstract: A pattern recognizing method and apparatus are arranged to detect one or more objects with its own individuality belonging to the same category, such as a vehicle or a human's face, by using incremental signs in a manner to correspond with an apparent change caused by the posture variation of the object. For achieving the pattern detection corresponding with the apparent change caused by the posture variation of the object, the statistic quality of the incremental signs is extracted from a database having image data of the objects. The learning of a feature vector composed by using the quality makes it possible to design the most approximate identifier for detecting a pattern.

Abstract: This invention is to provide a shape measuring device and a shape measuring method that can accurately measure a cross-sectional shape or a three-dimensional shape of a sample without using matching of characteristics. A shape measuring apparatus comprises a charged particle beam apparatus comprising a processor for measuring detected charged particles signal generated from the sample. The charged particle beam is irradiated to sample at first angle to generate a first signal and second angle to generate second signal. The processor selects a parameter indicating a relation between the first signal and a height of the sample or an inclination angle of the specimen until the first signal which achieves the second signal.

Abstract: An electron beam applied from an electron gun 1 and reflected off a surface of a specimen 7 placed on a stage 2 that is tilted at a tilt angle &phgr;=0 is detected, and a signal intensity thereof is measured by an electron detector 3. Based upon the measurement, an image processing unit 6 calculates a slope angle &thgr; of the surface of the specimen, and determines candidates for cross-sectional shape of the specimen. Signal intensity of the electromagnetic wave that would be reflected from a surface having a cross-sectional shape of each of the candidates if the tilt angle &phgr; were changed into &phgr;=&phgr;0 are estimated, and compared with a signal intensity actually measured by the electron detector 3 with the tilt angle &phgr; being changed into &phgr;=&phgr;0. Consequently, cross sectional shape and three-dimensional shape can be determined based upon a result of comparison, without utilizing a matching process of feature points.

Abstract: An electron beam applied from an electron gun 1 and reflected off a surface of a specimen 7 placed on a stage 2 that is tilted at a tilt angle &phgr;=0 is detected, and a signal intensity thereof is measured by an electron detector 3. Based upon the measurement, an image processing unit 6 calculates a slope angle &thgr; of the surface of the specimen, and determines candidates for cross-sectional shape of the specimen. Signal intensity of the electromagnetic wave that would be reflected from a surface having a cross-sectional shape of each of the candidates if the tilt angle &phgr; were changed into &phgr;=&phgr;0 are estimated, and compared with a signal intensity actually measured by the electron detector 3 with the tilt angle 100 being changed into &phgr;=&phgr;0. Consequently, cross sectional shape and three-dimensional shape can be determined based upon a result of comparison, without utilizing a matching process of feature points.

Abstract: An electron beam applied from an electron gun 1 and reflected off a surface of a specimen 7 placed on a stage 2 that is tilted at a tilt angle &phgr;=0 is detected, and a signal intensity thereof is measured by an electron detector 3. Based upon the measurement, an image processing unit 6 calculates a slope angle &thgr; of the surface of the specimen, and determines candidates for cross-sectional shape of the specimen. Signal intensity of the electromagnetic wave that would be reflected from a surface having a cross-sectional shape of each of the candidates if the tilt angle &phgr; were changed into &phgr;=&phgr;0 are estimated, and compared with a signal intensity actually measured by the electron detector 3 with the tilt angle 100 being changed into &phgr;=&phgr;0). Consequently, cross sectional shape and three-dimensional shape can be determined based upon a result of comparison, without utilizing a matching process of feature points.