Abstract: In an image processing device 300: a sign detection unit 303 detects a sign from an image; a sign distance calculating unit 307 calculates a distance D1 between a vehicle and the sign in the optical axis direction of an image pick-up device 100 and a distance D2 between the vehicle and the sign in the direction that crosses at right angles with the optical axis direction, based on the angle of coverage of the image pick-up device 100, the resolution of the image, the position and the size of the sign within the image, and the actual size of the sign; and a sign position estimating unit 309 estimates the position in which the sign is installed, based on the direction in which the vehicle progresses and the position of the vehicle at the time when the image is taken, and the distances D1 and D2.

Abstract: An abandoned item detection unit detects an abandoned item shown in an image taken by any of a plurality of imaging devices. A person identification unit specifies the image directly before or directly after the appearance of the abandoned item as an image of abandonment timing, and identifies at least one person shown in the image of abandonment timing as a target person. A person search unit searches for an image showing the target person from among the images respectively taken by any of the plurality of imaging devices. A result display unit outputs a display showing the movement of the target person on the screen of a user terminal on the basis of the imaging device that has taken each image showing the target person and the imaging time at which each image showing the target person was taken.

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 abandoned item detection unit detects an abandoned item shown in an image taken by any of a plurality of imaging devices. A person identification unit specifies the image directly before or directly after the appearance of the abandoned item as an image of abandonment timing, and identifies at least one person shown in the image of abandonment timing as a target person. A person search unit searches for an image showing the target person from among the images respectively taken by any of the plurality of imaging devices. A result display unit outputs a display showing the movement of the target person on the screen of a user terminal on the basis of the imaging device that has taken each image showing the target person and the imaging time at which each image showing the target person was taken.

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 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.