摘要:
In one embodiment of the invention, a pattern recognition apparatus comprises a unit for inputting a pattern of a to-be recognized category; and a processor with a memory for: generating input subspace; calculating and storing reference subspaces; storing constraint subspaces for extracting features; projecting the input subspace and the reference subspaces respectively onto the constraint subspaces; calculating similarities between the respective reference subspaces and the input subspace in such projected state; combining the similarities in respect of the constraint subspaces on each of the reference subspaces; and identifying the to-be recognized category with a category corresponding to one of the reference subspaces, if the combined similarity between the one of reference subspace and the input subspace is highest among them.
摘要:
In one embodiment of the invention, a pattern recognition apparatus comprises a unit for inputting a pattern of a to-be recognized category; and a processor with a memory for: generating input subspace; calculating and storing reference subspaces; storing constraint subspaces for extracting features; projecting the input subspace and the reference subspaces respectively onto the constraint subspaces; calculating similarities between the respective reference subspaces and the input subspace in such projected state; combining the similarities in respect of the constraint subspaces on each of the reference subspaces; and identifying the to-be recognized category with a category corresponding to one of the reference subspaces, if the combined similarity between the one of reference subspace and the input subspace is highest among them.
摘要:
A face recognition apparatus includes an image sequence acquiring unit, a face image acquiring unit, an intra-sequence classifying unit, an inter-sequence classifying unit, an identification unit, and a reference image storing unit. A plurality of cameras are attached in a corridor for monitoring one place with these cameras, so that when a plurality of moving people pass through, identification is performed for each moving people. Face images are classified into fragmental face image sets, and the fragmental face image sets are classified into integrated sets to achieve the identification.
摘要:
An object recognition apparatus in an embodiment includes an image input unit, an object detection unit, a diffuse reflection image generation unit, an object model storage unit, a difference image generation unit, a weight calculation unit, a weighted Gaussian filter application unit, a filter processing unit, and an identification unit. A weight to be assigned to a weighted Gaussian filter is determined in view of variations in lighting conditions and reflection components of pixels of an input image.
摘要:
An object is identified by detecting an object area image of an object to be recognized from a degraded image, converting the object area image to a frequency area, extracting a feature vector which indicates the amount of blur, comparing the feature vector and a classified plurality of blurred images, obtaining a cluster which is the most similar to the feature vector, selecting one point spread function corresponding to the similar cluster, restoring the object area image to the image before being blurred using the point spread function, and comparing the restored image and a target image.
摘要:
A face recognition apparatus includes an image sequence acquiring unit, a face image acquiring unit, an intra-sequence classifying unit, an inter-sequence classifying unit, an identification unit, and a reference image storing unit. A plurality of cameras are attached in a corridor for monitoring one place with these cameras, so that when a plurality of moving people pass through, identification is performed for each moving people. Face images are classified into fragmental face image sets, and the fragmental face image sets are classified into integrated sets to achieve the identification.
摘要:
An image input unit inputs an image including a user's face area to specify the user's gaze or face direction. A pattern generation unit generates an input pattern that can be compared with each dictionary pattern from the image. A dictionary unit previously stores a plurality of dictionary patterns each of which differently corresponds to the user's gaze or face direction. A pattern comparison unit respectively calculates a similarity degree between the input pattern and each of the dictionary patterns by comparing the input pattern with each of the dictionary patterns. A gaze detection unit detects the user's gaze or face direction based on the similarity degree.
摘要:
The present invention solves an eigenvalue problem using a sum of projection matrixes for each subspace. A space which is spanned by a plurality of eigenvectors which are selected starting from those having a smaller eigenvalue is used as a constraint subspace.
摘要:
An image processing apparatus. A camera inputs an image of a face of a person to be recognized. A recognition area detection section generates a difference image between the input image and a predetermined pattern, and detects a recognition area whose value is above a threshold from the input image. An input data generation section converts the recognition area to a predetermined input data. A similarity calculation section calculates a similarity by comparing the predetermined input data with a predetermined dictionary data. A view position of the camera is located lower than a position of the face of the person. A direction of the optical axis of the camera represents an angle of elevation from a horizontal direction.
摘要:
An image pattern of an object is inputted. An input subspace calculation section calculates an input subspace from the image pattern. A dictionary subspace calculation section calculates a dictionary subspace from a learning pattern of each object. A constraint subspace calculation means calculates a constraint subspace from a plurality of input subspaces previously calculated according to constraints to suppress unnecessary patterns. A projection section projects the input subspace and the dictionary subspace onto the constraint subspace. A recognition section recognizes the object by comparing the projected input subspace with the projected dictionary subspace.