Abstract: An information processing apparatus includes a face detection unit configured to detect a face of a person from an image; a storage unit configured to store dictionary data which holds information relating to faces and line-of-sight correction data corresponding to respective persons; an authentication unit configured to authenticate a person corresponding to the face detected by the face detection unit, using the information relating to faces in the dictionary data; a line-of-sight detection unit configured to detect information relating to a line of sight from the face detected by the face detection unit; and a line-of-sight correction unit configured to correct the information relating to a line of sight detected by the line-of-sight detection unit, using the line-of-sight correction data in the dictionary data corresponding to the person authenticated by the authentication unit.

Abstract: A facial expression recognition apparatus (10) detects a face image of a person from an input image, calculates a facial expression evaluation value corresponding to each facial expression from the detected face image, updates, based on the face image, the relationship between the calculated facial expression evaluation value and a threshold for determining a facial expression set for the facial expression evaluation value, and determines the facial expression of the face image based on the updated relationship between the facial expression evaluation value and the threshold for determining a facial expression.

Abstract: The present invention refers to an information processing apparatus comprising: an obtaining unit adapted to obtain an image of an object; a face region detection unit adapted to detect a face region of the object from the image; an eye region detection unit adapted to detect an eye region of the object; a generation unit adapted to generate a high-resolution image and low-resolution image of the face region detected by the face region detection means; a first extraction unit adapted to extract a first feature amount indicating a direction of a face existing in the face region from the low-resolution image; a second extraction unit adapted to extract a second feature amount indicating a direction of an eye existing in the eye region from the high-resolution image; and an estimation unit adapted to estimate a gaze direction of the object from the first feature amount and the second feature amount.

Abstract: An information processing apparatus inputs an image, detects the face of a person from the input image, and calculates a feature amount associated with the open/closed state of eyes of the detected face. In addition, the information processing apparatus calculates, as a feature-change amount, the difference between the calculated feature amount and a predetermined feature amount, and calculates the eye open/closed degree of eyes of the detected face on the basis of the feature amount and the feature-change amount.

Abstract: The present invention provides an agent which induces acceleration of hard tissue formation, acceleration of cell differentiation and increase in cellular alkaline phosphatase activity, by directly acting on the cell. Specifically, it provides a hard tissue formation promoter, a cell differentiation inducer and a cellular alkaline phosphatase activity reinforcing agent comprising, as an active ingredient, a glycosaminoglycan or a salt thereof that keeps sulfate group and has the characteristics of the following (1) and (2): (1) a basic structure is a disaccharide repeating structure consisting of a hexuronic acid residue and a glucosamine residue, (2) one or less of the position among a 2-position hydroxyl group of a hexuronic acid residue, a 6-position hydroxyl group of a glucosamine residue and a 2-position amino group of the glucosamine residue in the basic structure of the aforementioned (1) does not have the sulfate group.

Abstract: An information processing apparatus includes an image input unit which inputs image data containing a face, a face position detection unit which detects, from the image data, the position of a specific part of the face, and a facial expression recognition unit which detects a feature point of the face from the image data on the basis of the detected position of the specific part and determines facial expression of the face on the basis of the detected feature point. The feature point is detected at a detection accuracy higher than detection of the position of the specific part. Detection of the position of the specific part is robust to a variation in the detection target.

Abstract: An image including a face is input (S201), a plurality of local features are detected from the input image, a region of a face in the image is specified using the plurality of detected local features (S202), and an expression of the face is determined on the basis of differences between the detection results of the local features in the region of the face and detection results which are calculated in advance as references for respective local features in the region of the face (S204).

Abstract: A situation monitoring device which enables monitoring of a variety of situations and reporting in response to the situation using a single device is provided. The situation monitoring device is easy to install and to use and a system therefore can be implemented inexpensively. The situation monitoring device recognizes a place or installation where the device is installed (step S102), holds relational information correlating the place of installation and the situation to be recognized and determines a predetermined situation to be recognized according to place of installation recognition results and the relational information (step S104), recognizes a determined predetermined situation (step S106), and reports the result of the predetermined situation to a user (step S108).

Abstract: An information processing apparatus includes an image input unit which inputs image data containing a face, a face position detection unit which detects, from the image data, the position of a specific part of the face, and a facial expression recognition unit which detects a feature point of the face from the image data on the basis of the detected position of the specific part and determines facial expression of the face on the basis of the detected feature point. The feature point is detected at a detection accuracy higher than detection of the position of the specific part. Detection of the position of the specific part is robust to a variation in the detection target.

Abstract: An image-processing apparatus for executing accurate facial expression recognition even for a subject hard to recognize a facial expression is provided. A person's face region is extracted from an image input from an image input unit. A predetermined partial region that changes between when the facial expression is in the first and second states is extracted from the extracted face region. A facial expression evaluation value is calculated using an evaluation value calculation formula. When the calculated facial expression evaluation value exceeds a threshold value, it is determined that the facial expression is in the second state. If the difference between the maximum value and the minimum value of the calculated facial expression evaluation value within a predetermined time is smaller than a predetermined value, the evaluation value calculation formula or its parameter is changed to increase the difference.

Abstract: In a pattern identification method in which input data is classified into predetermined classes by sequentially executing a combination of a plurality of classification processes, at least one of the classification processes includes a mapping step of mapping the input data in an N (N?2) dimensional feature space as corresponding points, a determination step of determining whether or not to execute the next classification process based on the corresponding points, and selecting step of selecting a classification process to be executed next based on the corresponding points when it is determined in the determination step that the next classification process should be executed.

Abstract: An image including a face is input (S201), a plurality of local features are detected from the input image, a region of a face in the image is specified using the plurality of detected local features (S202), and an expression of the face is determined on the basis of differences between the detection results of the local features in the region of the face and detection results which are calculated in advance as references for respective local features in the region of the face (S204).

Abstract: A feature point detection unit (153) and feature amount extraction unit (154) extract a plurality of features of an object from input image data. When there are unextracted features of the plurality of features, a weight setting unit (155) sets weights for the extracted features. A facial expression determination unit (156) executes recognition processing of the object based on the features weighted by the weight setting unit (155).

Abstract: A person is detected as a subject from an image obtained by image capture, and information, for example, the number of such subjects, is obtained as subject-related information. Then, the greater the number of subjects, the more a setting of a condition that the subjects should satisfy is relaxed. As a result, in an image processing apparatus having a function that identifies a subject state, the usability of that function that identifies the subjects can be improved even in a case in which multiple subjects are present.

Abstract: A learning apparatus for a pattern detector, which includes a plurality of weak classifiers and detects a specific pattern from input data by classifications of the plurality of weak classifiers, acquires a plurality of data for learning in each of which whether or not the specific pattern is included is given, makes the plurality of weak classifiers learn by making the plurality of weak classifiers detect the specific pattern from the acquired data for learning, selects a plurality of weak classifiers to be composited from the weak classifiers which have learned, and composites the plurality of weak classifiers into one composite weak classifier based on comparison between a performance of the composite weak classifier and performances of the plurality of weak classifiers.

Abstract: An information processing apparatus includes a face detection unit configured to detect a face of a person from an image; a storage unit configured to store dictionary data which holds information relating to faces and line-of-sight correction data corresponding to respective persons; an authentication unit configured to authenticate a person corresponding to the face detected by the face detection unit, using the information relating to faces in the dictionary data; a line-of-sight detection unit configured to detect information relating to a line of sight from the face detected by the face detection unit; and a line-of-sight correction unit configured to correct the information relating to a line of sight detected by the line-of-sight detection unit, using the line-of-sight correction data in the dictionary data corresponding to the person authenticated by the authentication unit.

Abstract: An information processing apparatus comprising: an obtaining unit configured to obtain image data; a detection unit configured to detect an object from the image data; an attribute determination unit configured to determine an attribute indicating a characteristic of the object detected by the detection unit; a registration unit configured to register the image data in at least one of a plurality of dictionaries based on the attribute determined by the attribute determination unit; and an adding unit configured to add, when the image data is registered in not less than two dictionaries, link information concerning the image data registered in the other dictionary to the image data registered in one dictionary.

Abstract: An eye region is detected, in the detected eye region, the region of an iris outline is extended inward, and a hollow region surrounded by the extended region is detected as a poor hue quality region. An outline of the poor hue quality region is shaped by approximating the outline to one of a circle and an ellipse. The hue of the shaped poor hue quality region is corrected on the basis of color information obtained from a neighboring region inside an iris outline.

Abstract: A facial expression recognition apparatus includes an image input unit configured to sequentially input images, a face detection unit configured to detect faces in images obtained by the image input unit, and a start determination unit configured to determine whether to start facial expression determination based on facial image information detected by the face detection unit. When the start determination unit determines that facial expression determination should be started, an acquisition unit acquires reference feature information based on the facial image information detected by the face detection unit and a facial expression determination unit extracts feature information from the facial image information detected by the face detection unit and determines facial expressions of the detected faces based on the extracted feature information and the reference feature information.

Abstract: A line-of-sight detection apparatus includes a detection unit configured to detect a face from image data, a first extraction unit configured to extract a feature amount corresponding to a direction of the face from the image data, a calculation unit configured to calculate a line-of-sight reliability of each of a right eye and a left eye based on the face, a selection unit configured to select an eye according to the line-of-sight reliability, a second extraction unit configured to extract a feature amount of an eye region of the selected eye from the image data, and an estimation unit configured to estimate a line of sight of the face based on the feature amount corresponding to the face direction and the feature amount of the eye region.