Abstract: The purpose of the present invention is to provide a technology which adaptively switches video analysis methods according to a congestion situation within a video, and which carries out a suitable video analysis by a limited computational volume. Provided is an image processing device 100, wherein a congestion estimation unit 102 estimates a congestion situation within a video which is acquired from an image input unit 101. A control unit 103 switches methods for video analysis according to the congestion situation. In a situation of low congestion, an image analysis unit for use in normal situations 105 carries out the video analysis by a basic method. In a situation of high congestion, an image analysis unit for use in congested situations 106 carries out a high-precision video analysis, such as an analysis which spans a plurality of frames.

Abstract: An image monitoring system includes: a reference image generation unit generating a reference image serving as a reference image, based on an input image; a foreground extraction unit detecting, from the input image, a foreground region different from the reference image; a stationary region extraction unit extracting a stationary region from the foreground region; a feature quantity extraction unit extracting a feature quantity of the stationary region; a feature quantity recording unit recording feature quantities as a function of time; a stationary object detection unit clustering pixels, recorded feature quantities of which meet predetermined criteria, and detecting a stationary object; a left object determination unit determining whether the stationary object is a left object, based on a feature quantity of the stationary object and evaluation of the surrounding environment; and a left object management unit managing attributes of left objects, and issuing a report when a certain condition is met.

Abstract: Provided is an epitaxial wafer having an excellent gettering capability and a suppressed formation of epitaxial defects. The epitaxial wafer has a specified resistivity, and includes a modifying layer formed on a surface portion of the silicon wafer and composed of a predetermined element including at least carbon, in the form of a solid solution in the silicon wafer; and an epitaxial layer having a resistivity that is higher than the resistivity of the silicon wafer, wherein a concentration profile of the predetermined element in the modifying layer in a depth direction thereof meets a specified full width half maximum and a specified peak concentration.

Abstract: The present invention provides a system for visualizing the congestion degree of an entire facility using a monitoring camera. The system detects a crowd from a monitoring camera video and derives the magnitude (number of people) of the crowd from the edge amount thereof, and thereby estimates a congestion state in a range of camera video. The system also calculates a human flow (amount of movement of people) on the basis of a number of passing people counter and the magnitude and movement speed of the crowd, etc., and estimates the number of people in an area other than the range of camera video on the basis of a modeled crowd behavior pattern. The model is constructed by selecting a distribution function and a parameter thereof by a statistical model selection technique such as a Bayesian Information Criteria (BIC). The congestion state is plotted on a map, allowing the congestion state of an area of interest to be grasped at once.

Abstract: An image monitoring system includes: a reference image generation unit generating a reference image serving as a reference image, based on an input image; a foreground extraction unit detecting, from the input image, a foreground region different from the reference image; a stationary region extraction unit extracting a stationary region from the foreground region; a feature quantity extraction unit extracting a feature quantity of the stationary region; a feature quantity recording unit recording feature quantities as a function of time; a stationary object detection unit clustering pixels, recorded feature quantities of which meet predetermined criteria, and detecting a stationary object; a left object determination unit determining whether the stationary object is a left object, based on a feature quantity of the stationary object and evaluation of the surrounding environment; and a left object management unit managing attributes of left objects, and issuing a report when a certain condition is met.

Abstract: The purpose of the present invention is to provide a technology which adaptively switches video analysis methods according to a congestion situation within a video, and which carries out a suitable video analysis by a limited computational volume. Provided is an image processing device 100, wherein a congestion estimation unit 102 estimates a congestion situation within a video which is acquired from an image input unit 101. A control unit 103 switches methods for video analysis according to the congestion situation. In a situation of low congestion, an image analysis unit for use in normal situations 105 carries out the video analysis by a basic method. In a situation of high congestion, an image analysis unit for use in congested situations 106 carries out a high-precision video analysis, such as an analysis which spans a plurality of frames.

Abstract: A system detects a candidate for an object which intrudes based on images of a visible light camera and a far-infrared camera that monitor the sea, further derives a size, a velocity, an intrusion direction, and linearity, and identifies the object to some extent. Also, the system distinguishes between a boat, a human, and a floating matter based on the luminances or the like in a far-infrared image. In addition, the system observes the periodicity of normal waves on the sea surface at a location without any object by performing the Fourier transform on the image. The accuracy of identification of an object is improved based on the correlation between the motion of waves in a normal state and the motion of the object.

Abstract: A system detects a candidate for an object which intrudes based on images of a visible light camera and a far-infrared camera that monitor the sea, further derives a size, a velocity, an intrusion direction, and linearity, and identifies the object to some extent. Also, the system distinguishes between a boat, a human, and a floating matter based on the luminances or the like in a far-infrared image. In addition, the system observes the periodicity of normal waves on the sea surface at a location without any object by performing the Fourier transform on the image. The accuracy of identification of an object is improved based on the correlation between the motion of waves in a normal state and the motion of the object.

Abstract: The present invention provides a system for visualizing the congestion degree of an entire facility using a monitoring camera. The system detects a crowd from a monitoring camera video and derives the magnitude (number of people) of the crowd from the edge amount thereof, and thereby estimates a congestion state in a range of camera video. The system also calculates a human flow (amount of movement of people) on the basis of a number of passing people counter and the magnitude and movement speed of the crowd, etc., and estimates the number of people in an area other than the range of camera video on the basis of a modeled crowd behavior pattern. The model is constructed by selecting a distribution function and a parameter thereof by a statistical model selection technique such as a Bayesian Information Criteria (BIC). The congestion state is plotted on a map, allowing the congestion state of an area of interest to be grasped at once.

Abstract: The present invention provides a crowd monitoring system with which it is possible to obtain a crowd density accurately, irrespective of the congestion state. This crowd monitoring system 100 is provided with: an image acquiring unit 101 which acquires a plurality of images; an arithmetic logic unit 108; and a storage unit 106 which stores information relating to relationships between image feature quantities and an object density, acquired in advance, and information relating to relationships between motion feature quantities and the object density. The arithmetic logic unit 108 comprises: an image feature quantity acquiring unit 103 which obtains image feature quantities of objects in the acquired images; a motion line acquiring unit 104 which obtains motion lines of the objects in the acquired images; a motion feature quantity acquiring unit 105 which obtains motion feature quantities of the objects on the basis of the obtained motion lines; and a crowd density acquiring unit 107.

Abstract: A wireless device includes an imaging unit having an optical axis which is identical to a radio wave direction of a directional antenna, a reference image is stored in a storage unit, a wireless communication device serving as a communication counterpart and an area around the wireless communication device are photographed at regular intervals, and a control unit compares images photographed at regular intervals with a reference image, calculates a degree of similarity through normalized cross-correlation which is hardly influenced by a change in brightness, calculates an index value indicating a state of a region serving as a monitoring target based on a degree of weighted similarity, detects an abnormality when the index value is a specific numerical value or less, and outputs alert information including the photographed image when a state in which the abnormality is detected is continued for a certain period of time.

Abstract: This crowd monitoring system (MS) is provided with: a storage unit in which a plurality of images of a crowd including moving bodies are stored; a feature-value extraction unit which extracts a feature of each image; a number of persons input image selection unit which takes into account the distribution of the features, and selects, from among the images, a sample image for inputting the number of persons among the moving bodies; the number of persons input reception unit which displays, on a display unit, an input screen for inputting the number of persons among the moving bodies in the sample image, and receives an input of the number of persons among the moving bodies in the sample image; and a feature total number function generation unit which generates a function indicating the relationship between the features and the total number among the moving bodies.

Abstract: The present invention provides a crowd monitoring system with which it is possible to obtain a crowd density accurately, irrespective of the congestion state. This crowd monitoring system 100 is provided with: an image acquiring unit 101 which acquires a plurality of images; an arithmetic logic unit 108; and a storage unit 106 which stores information relating to relationships between image feature quantities and an object density, acquired in advance, and information relating to relationships between motion feature quantities and the object density. The arithmetic logic unit 108 comprises: an image feature quantity acquiring unit 103 which obtains image feature quantities of objects in the acquired images; a motion line acquiring unit 104 which obtains motion lines of the objects in the acquired images; a motion feature quantity acquiring unit 105 which obtains motion feature quantities of the objects on the basis of the obtained motion lines; and a crowd density acquiring unit 107.

Abstract: A wireless device includes an imaging unit having an optical axis which is identical to a radio wave direction of a directional antenna, a reference image is stored in a storage unit, a wireless communication device serving as a communication counterpart and an area around the wireless communication device are photographed at regular intervals, and a control unit compares images photographed at regular intervals with a reference image, calculates a degree of similarity through normalized cross-correlation which is hardly influenced by a change in brightness, calculates an index value indicating a state of a region serving as a monitoring target based on a degree of weighted similarity, detects an abnormality when the index value is a specific numerical value or less, and outputs alert information including the photographed image when a state in which the abnormality is detected is continued for a certain period of time.

Abstract: This crowd monitoring system (MS) is provided with: a storage unit in which a plurality of images of a crowd including moving bodies are stored; a feature-value extraction unit which extracts a feature of each image; a number of persons input image selection unit which takes into account the distribution of the features, and selects, from among the images, a sample image for inputting the number of persons among the moving bodies; the number of persons input reception unit which displays, on a display unit, an input screen for inputting the number of persons among the moving bodies in the sample image, and receives an input of the number of persons among the moving bodies in the sample image; and a feature total number function generation unit which generates a function indicating the relationship between the features and the total number among the moving bodies.

Abstract: In a monitoring apparatus for monitoring an object which intrudes into a monitoring subject area by using an image pickup device, it is demanded to adjust parameters according to conditions such as the monitoring purpose and the surrounding environment in order to execute suitable monitoring. To this end, in the monitoring apparatus, parameters corresponding to monitoring conditions are subject to grouping. Suitable values of parameters in each group obtained by the grouping are previously determined according to a degree of a monitoring condition. A monitoring condition and its degree are selected by using an ordering device having user interface components such as push buttons mounted thereon. It is made possible to instantaneously alter parameters belonging to a group corresponding to the monitoring condition all at once at this time. Parameter adjustment free from troublesomeness and skill is thus implemented.

Abstract: Binarization is performed using a threshold image obtained by multiplying a variation in each pixel value of an input image with a coefficient. Although the variation is time-averaged based on an update coefficient for each pixel, the update coefficient is switched depending on whether or not a relevant pixel belongs to the object. Subsequently, from the binary image, an initial detection zone is formed and a spatial filtering process is performed thereto. The spatial filtering process includes at least one of skeleton analysis processing, object mask processing, morphology processing, and section analysis processing. For a tracking zone, the temporal positional change thereof is tracked, and the noise is reduced. Some of the tracking zones are removed, and the remaining zones are integrated into a cluster, and furthermore the cluster selection is performed based on the dimensions in real space.

Abstract: Binarization is performed using a threshold image obtained by multiplying a variation in each pixel value of an input image with a coefficient. Although the variation is time-averaged based on an update coefficient for each pixel, the update coefficient is switched depending on whether or not a relevant pixel belongs to the object. Subsequently, from the binary image, an initial detection zone is formed and a spatial filtering process is performed thereto. The spatial filtering process includes at least one of skeleton analysis processing, object mask processing, morphology processing, and section analysis processing. For a tracking zone, the temporal positional change thereof is tracked, and the noise is reduced. Some of the tracking zones are removed, and the remaining zones are integrated into a cluster, and furthermore the cluster selection is performed based on the dimensions in real space.

Abstract: In a monitoring apparatus for monitoring an object which intrudes into a monitoring subject area by using an image pickup device, it is demanded to adjust parameters according to conditions such as the monitoring purpose and the surrounding environment in order to execute suitable monitoring. To this end, in the monitoring apparatus, parameters corresponding to monitoring conditions are subject to grouping. Suitable values of parameters in each group obtained by the grouping are previously determined according to a degree of a monitoring condition. A monitoring condition and its degree are selected by using an ordering device having user interface components such as push buttons mounted thereon. It is made possible to instantaneously alter parameters belonging to a group corresponding to the monitoring condition all at once at this time. Parameter adjustment free from troublesomeness and skill is thus implemented.