Abstract: An information processing unit includes: a diagnostic image input section that inputs the diagnostic image; an operation information obtaining section that obtains display operation history information representing an operation history of a user who controls displaying of the diagnostic image; a query image generation section that extracts a predetermined region of the input diagnostic image to generate a query image; a diagnosed image obtaining section that supplies the generated query image and the display operation history information to a diagnosed image search unit and obtains the diagnosed image obtained as a search result by the diagnosed image search unit; and a display control section that displays the diagnostic image and the obtained diagnosed image for comparison.

Abstract: An image processing system includes a storing section that stores a database in which specific pose data representing each of specific poses of a human, and effect manipulation data specifying each of manipulations applied to an image are registered in association with each other, a human region detecting section that detects a human region that is a region where a human appears in an image on which to perform image processing, a human pose recognizing section that recognizes a pose of the human in the human region detected by the human region detecting section, a matching section that finds the specific pose data matching the pose recognized by the human pose recognizing section, by referencing the database, and a manipulating section that applies a manipulation to the image on the basis of the effect manipulation data associated with the specific pose data found by the matching section.

Abstract: An information processing device includes: an outline extraction unit extracting an outline of a subject from a picked-up image of the subject; a characteristic amount extraction unit extracting a characteristic amount, by extracting sample points from points making up the outline, for each of the sample points; an estimation unit estimating a posture of a high degree of matching as a posture of the subject by calculating a degree of the characteristic amount extracted in the characteristic amount extraction unit being matched with each of a plurality of characteristic amounts that are prepared in advance and represent predetermined postures different from each other; and a determination unit determining accuracy of estimation by the estimation unit using a matching cost when the estimation unit carries out the estimation.

Abstract: An information processing device includes a feature amount extraction unit configured to extract each feature amount from a connected image generated by connecting images photographed from different viewpoints; and a specific object recognition unit configured to perform a process of determining a position of a specific object based on the feature amount extracted by the feature amount extraction unit. The feature amount extraction unit performs a feature amount extraction process to which a separated filter in which filter-formed regions are set to be separated is applied.

Abstract: An information processing device includes: an outline extraction unit extracting an outline of a subject from a picked-up image of the subject; a characteristic amount extraction unit extracting a characteristic amount, by extracting sample points from points making up the outline, for each of the sample points; an estimation unit estimating a posture of a high degree of matching as a posture of the subject by calculating a degree of the characteristic amount extracted in the characteristic amount extraction unit being matched with each of a plurality of characteristic amounts that are prepared in advance and represent predetermined postures different from each other; and a determination unit determining accuracy of estimation by the estimation unit using a matching cost when the estimation unit carries out the estimation.

Abstract: An image processing device includes a difference image generation unit which generates a difference image by obtaining a difference between frames of a cutout image which is obtained by cutting out a predetermined region on a photographed image; a feature amount extracting unit which extracts a feature amount from the difference image; and a recognition unit which recognizes a specific movement of an object on the photographed image based on the feature amount which is obtained from the plurality of difference images which are aligned in time sequence.

Abstract: A learning device includes: a generating unit configured to generate an image having different resolution from an input image; an extracting unit configured to extract a feature point serving as a processing object from an image generated by the generating unit; a calculating unit configured to calculate the feature amount of the feature point by subjecting the feature point to filter processing employing a predetermined filter; and an identifier generating unit configured to generate an identifier for detecting a predetermined target object from the image by statistical learning employing the feature amount; with the filter including a plurality of regions, and the calculating unit taking the difference value of difference within the regions as the feature amount.

Abstract: A natural user interface system and method of operation thereof including: a display device having a display screen and a display device camera; a mobile device having a mobile device camera, an optical axis of the mobile device camera positioned at an angle to an optical axis of the display device camera; wherein: the mobile device includes a first device pairing module for pairing the mobile device with the display device; the mobile device camera and the display device camera are for: detecting a user's hand, and determining posture and movement of the user's hand; and the display device includes a motion translation module for translating the posture and movement of the user's hand into a gesture for controlling an element of a user interface on the display screen.

Abstract: An information processing apparatus includes circuitry that is configured to provide a user interface to control a plurality of controllable objects. The user interface is associated with a gesture recognition area that is defined by a predetermined detection area of a sensor. The gesture recognition area is divided into a plurality of gesture recognition sub-areas based on a number of the controllable objects to be controlled by the user interface. The circuitry is further configured to detect a predetermined gesture within the predetermined detection area, determine the gesture recognition sub-area in which the predetermined gesture is detected, and perform an operation on one of the controllable objects based on the detected predetermined gesture and the determined gesture recognition sub-area in which the predetermined gesture is detected.

Abstract: Systems and methods for implementing a hierarchical image recognition framework for classifying digital images are provided. The provided hierarchical image recognition framework utilizes a multi-layer approach to model training and image classification tasks. A first layer of the hierarchical image recognition framework generates first layer confidence scores, which are utilized by the second layer to produce a final recognition score. The provided hierarchical image recognition framework permits model training and image classification tasks to be performed more accurately and in a less resource intensive fashion than conventional single-layer image recognition frameworks. In some embodiments real-time operator guidance is provided for an image classification task.

Abstract: An information processing unit includes: a diagnostic image input section that inputs the diagnostic image; an operation information obtaining section that obtains display operation history information representing an operation history of a user who controls displaying of the diagnostic image; a query image generation section that extracts a predetermined region of the input diagnostic image to generate a query image; a diagnosed image obtaining section that supplies the generated query image and the display operation history information to a diagnosed image search unit and obtains the diagnosed image obtained as a search result by the diagnosed image search unit; and a display control section that displays the diagnostic image and the obtained diagnosed image for comparison.

Abstract: An integrated interactive segmentation with spatial constraint method utilizes a combination of several of the most popular online learning algorithms into one and implements a spatial constraint which defines a valid mask local to the user's given marks. Additionally, both supervised learning and statistical analysis are integrated, which are able to compensate each other. Once prediction and activation are obtained, pixel-wised multiplication is conducted to fully indicate how likely each pixel belongs to the foreground or background.

Abstract: An image processing device includes a difference image generation unit which generates a difference image by obtaining a difference between frames of a cutout image which is obtained by cutting out a predetermined region on a photographed image; a feature amount extracting unit which extracts a feature amount from the difference image; and a recognition unit which recognizes a specific movement of an object on the photographed image based on the feature amount which is obtained from the plurality of difference images which are aligned in time sequence.

Abstract: Disclosed is a learning device. A feature-quantity calculation unit extracts a feature quantity from each feature point of a learning image. An acquisition unit acquires a classifier already obtained by learning as a transfer classifier. A classifier generation unit substitutes feature quantities into weak classifiers constituting the transfer classifier, calculates error rates of the weak classifiers on the basis of classification results of the weak classifiers and a weight of the learning image, and iterates a process of selecting a weak classifier of which the error rate is minimized a plurality of times. In addition, the classifier generation unit generates a classifier for detecting a detection target by linearly coupling a plurality of selected weak classifiers.

Abstract: There is provided an image processing device including a movement section which scrolls a medical image on a screen, and a display control section which, in a case where the medical image is scrolled on the screen, controls a display section to display the medical image in a manner that an observation reference position of a diagnosis region of the medical image passes through a display reference position of a display region of the screen.

Abstract: An image processing system includes a storing section that stores a database in which specific pose data representing each of specific poses of a human, and effect manipulation data specifying each of manipulations applied to an image are registered in association with each other, a human region detecting section that detects a human region that is a region where a human appears in an image on which to perform image processing, a human pose recognizing section that recognizes a pose of the human in the human region detected by the human region detecting section, a matching section that finds the specific pose data matching the pose recognized by the human pose recognizing section, by referencing the database, and a manipulating section that applies a manipulation to the image on the basis of the effect manipulation data associated with the specific pose data found by the matching section.

Abstract: An information processing device includes a feature amount extraction unit configured to extract each feature amount from a connected image generated by connecting images photographed from different viewpoints; and a specific object recognition unit configured to perform a process of determining a position of a specific object based on the feature amount extracted by the feature amount extraction unit. The feature amount extraction unit performs a feature amount extraction process to which a separated filter in which filter-formed regions are set to be separated is applied.

Abstract: An information processing device includes a data processing unit that executes analysis of images which are captured from different viewpoints. The data processing unit executes an object distance calculation process in which pattern-irradiated images of a plurality of different viewpoints are applied, and an object detection process in which non-pattern-irradiated images are applied.

Abstract: A learning device includes: a generating unit configured to generate an image having different resolution from an input image; an extracting unit configured to extract a feature point serving as a processing object from an image generated by the generating unit; a calculating unit configured to calculate the feature amount of the feature point by subjecting the feature point to filter processing employing a predetermined filter; and an identifier generating unit configured to generate an identifier for detecting a predetermined target object from the image by statistical learning employing the feature amount; with the filter including a plurality of regions, and the calculating unit taking the difference value of difference within the regions as the feature amount.

Abstract: Disclosed is a learning device. A feature-quantity calculation unit extracts a feature quantity from each feature point of a learning image. An acquisition unit acquires a classifier already obtained by learning as a transfer classifier. A classifier generation unit substitutes feature quantities into weak classifiers constituting the transfer classifier, calculates error rates of the weak classifiers on the basis of classification results of the weak classifiers and a weight of the learning image, and iterates a process of selecting a weak classifier of which the error rate is minimized a plurality of times. In addition, the classifier generation unit generates a classifier for detecting a detection target by linearly coupling a plurality of selected weak classifiers.