Abstract: A person-judging device comprises: an obstruction storage which stores information indicating an area of an obstruction which is extracted from an image based on a video signal from an external camera, the obstruction being extracted from the image; head portion range calculation means which, when a portion of an object which is extracted from the image is hidden by the obstruction, assumes that a potential range of grounding points where the object touches a reference face on the image is the area of the obstruction which is stored in the obstruction storage, and which, based on the assumed range and the correlation between the height of a person and the size and position of the head portion that are previously provided, calculates the potential range of the head portion on the image by assuming that a portion farthest from the grounding points of the object is the head portion of the person; and head portion detection means that judges whether an area including a shape corresponding to the head portion exis

Abstract: A learning apparatus in the present invention includes a weak discriminator generation unit that generates a weak discriminator which calculates a discrimination score of an instance of a target based on a feature and a bag label, a weak discrimination unit which calculates the discrimination score based on the generated weak discriminator, an instance probability calculation unit that calculates an instance probability of the target instance based on the calculated the discrimination score, a bag probability calculation unit that calculates a probability that no smaller than two positive instances are included in the bag based on the calculated instance probability and a likelihood calculation unit which calculates likelihood representing plausibility of the bag probability based on the bag label.

Abstract: An object recognition system in which fall of the recognition rate is suppressed when an object is recognized based on an image even if there is a partial concealment and the object can be recognized even if the region of concealment is large with large calculation amount. With regard to each of a plurality of partial regions of an object image, partial recognition score of recognition object category is determined by judging whether it is a recognition object category or not. Under a condition that it is a recognition object category, total score is calculated using the total product of nonoccurrence probability of the partial recognition score, and a judgment is made that the object is not a recognition object category by that total score.

Abstract: A learning device includes a gradient feature extraction unit which extracts a gradient feature amount including a gradient direction at each coordinate and a gradient intensity value thereof based on an amount of variation between luminance at each coordinate of an inputted learning target pattern and luminance at a periphery thereof, a sum difference feature extraction unit which calculates a predetermined sum difference feature amount by adding the gradient intensity values according to the gradient directions included in a predetermined gradient range indicating a range of the predetermined gradient direction based on the extracted gradient feature amount and subtracting the gradient intensity values according to the gradient directions included in the other gradient range adjacent to the predetermined gradient range from the calculated sum, and a learning unit which acquires a learning parameter at each coordinate.

Abstract: It is to learn an object identification parameter while suppressing an influence of the background area. The object identification parameter learning system includes: a feature extracting device for obtaining a feature of an object from the image; a background specifying device for specifying a background area of the image; a background replacing device which replaces feature components corresponding to the background area of the feature with other values; and an identification parameter update device for updating the identification parameter based on the feature components replaced by the background replacing device. The identification parameter can be learnt by generating a plurality of pieces of feature data of the object with different backgrounds from a single object image through replacing the background area of the feature of the object.

Abstract: A person-judging device comprises: an obstruction storage which stores information indicating an area of an obstruction which is extracted from an image based on a video signal from an external camera, the obstruction being extracted from the image; head portion range calculation means which, when a portion of an object which is extracted from the image is hidden by the obstruction, assumes that a potential range of grounding points where the object touches a reference face on the image is the area of the obstruction which is stored in the obstruction storage, and which, based on the assumed range and the correlation between the height of a person and the size and position of the head portion that are previously provided, calculates the potential range of the head portion on the image by assuming that a portion farthest from the grounding points of the object is the head portion of the person; and head portion detection means that judges whether an area including a shape corresponding to the head portion exis

Abstract: Unauthorized use of a biological pattern registered in a face image authorization system is made difficult. With respect to the previously registered biological pattern for authorization, additional information is held concerning a change that can be reproduced by a user having the biological pattern for authentication, and success or failure of the authentication is evaluated according to consistency between the biological pattern for authentication that is reproduced using the additional information and a pattern input at the time of authentication as an evaluation factor. By changing the additional information as necessary, unauthorized use of biological pattern data or the like is made difficult.

Abstract: A discriminative data learning system provided comprises a learning device for updating dictionary data having a template to be used for discriminating the category of a hierarchical structure, and a discriminating device for classifying a pattern into a category with reference to the dictionary data.

Abstract: An object recognition system in which fall of the recognition rate is suppressed when an object is recognized based on an image even if there is a partial concealment and the object can be recognized even if the region of concealment is large with large calculation amount. With regard to each of a plurality of partial regions of an object image, partial recognition score of recognition object category is determined by judging whether it is a recognition object category or not. Under a condition that it is a recognition object category, total score is calculated using the total product of nonoccurrence probability of the partial recognition score, and a judgment is made that the object is not a recognition object category by that total score.

Abstract: In masquerading determination processing, a masquerading determination unit reads image data representing an image of an identification target on which a striped pattern is projected from an image storage unit to extract the striped pattern appearing in a face region of the image represented by the read image data. Subsequently, the masquerading determination unit determines whether a stripe in the face region in the image is a straight line or not. When the stripe is a straight line, because the identification target is a plane object such as a photograph or an image display device so that it can be determined that the target is at least not a person himself, the masquerading determination unit determines that the target masquerades. On the other hand, unless the stripe is a straight line, because the identification target has a solid configuration having three-dimensional irregularities to have a possibility of being a person himself, the unit determines that the target might not masquerade.

Abstract: A discriminative data learning system provided comprises a learning device (10) for updating dictionary data having a template to be used for discriminating the category of a hierarchical structure, and a discriminating device (20) for classifying a pattern into a category with reference to the dictionary data.

Abstract: It is to learn an object identification parameter while suppressing an influence of the background area. The object identification parameter learning system includes: a feature extracting device for obtaining a feature of an object from the image; a background specifying device for specifying a background area of the image; a background replacing device which replaces feature components corresponding to the background area of the feature with other values; and an identification parameter update device for updating the identification parameter based on the feature components replaced by the background replacing device. The identification parameter can be learnt by generating a plurality of pieces of feature data of the object with different backgrounds from a single object image through replacing the background area of the feature of the object.

Abstract: In masquerading determination processing, a masquerading determination unit reads image data representing an image of an identification target on which a striped pattern is projected from an image storage unit to extract the striped pattern appearing in a face region of the image represented by the read image data. Subsequently, the masquerading determination unit determines whether a stripe in the face region in the image is a straight line or not. When the stripe is a straight line, because the identification target is a plane object such as a photograph or an image display device so that it can be determined that the target is at least not a person himself, the masquerading determination unit determines that the target masquerades. On the other hand, unless the stripe is a straight line, because the identification target has a solid configuration having three-dimensional irregularities to have a possibility of being a person himself, the unit determines that the target might not masquerade.