摘要:
A learning device includes: a feature point extracting unit for extracting a feature point from each of multiple generated images; a feature point feature amount extracting unit for extracting feature point feature amount representing the feature of the feature point from the generated image; a whole feature amount calculating unit for calculating the whole feature amount representing the feature of the whole generated image from the feature point feature amount of the generated image based on a shared code book including generated feature amount to be commonly used for generation of an identifier for identifying each of different identified objects; and an identifier generating unit for generating the identifier based on the whole feature amount of the generated image, and a correct answer label representing whether the generated image is the positive image or the negative image.
摘要:
A learning device includes: a feature point extracting unit for extracting a feature point from each of multiple generated images made up of a positive image including an identified object, and a negative image excluding the identified object; a feature point feature amount extracting unit for extracting feature point feature amount representing the feature of the feature point from the generated image; a whole feature amount calculating unit for calculating the whole feature amount representing the feature of the whole generated image based on the feature point feature amount of a feature point existing on a feature point selection range determined based on the multiple generated images, of the generated image range; and an identifier generating unit for generating an identifier based on the whole feature amount of the generated image, and a correct answer label representing whether the generated image is the positive image or the negative image.
摘要:
A learning device includes: a feature point extracting unit for extracting a feature point from each of multiple generated images made up of a positive image including an identified object, and a negative image excluding the identified object; a feature point feature amount extracting unit for extracting feature point feature amount representing the feature of the feature point from the generated image; a whole feature amount calculating unit for calculating the whole feature amount representing the feature of the whole generated image based on the feature point feature amount of a feature point existing on a feature point selection range determined based on the multiple generated images, of the generated image range; and an identifier generating unit for generating an identifier based on the whole feature amount of the generated image, and a correct answer label representing whether the generated image is the positive image or the negative image.
摘要:
A learning apparatus includes a learning section which learns, according as a learning image used for learning a discriminator for discriminating whether a predetermined discrimination target is present in an image is designated from a plurality of sample images by a user, the discriminator using a random feature amount including a dimension feature amount randomly selected from a plurality of dimension feature amounts included in an image feature amount indicating features of the learning image.
摘要:
An apparatus for sharing virtual objects may include a communication unit and a sharing control unit. The communication unit may be configured to receive position data indicating a position of a virtual object relative to a real space. The sharing control unit may be configured to compare the position of the virtual object to a sharing area that is defined relative to the real space. The sharing control unit may also be configured to selectively permit display of the virtual object by a display device, based on a result of the comparison.
摘要:
A camera calibration device capable of simply calibrating a stereo system consisting of a base camera and detection camera. First, distortion parameters of the two cameras necessary for distance measurement are presumed by the use of images obtained by shooting a patterned object plane with the base camera and the reference camera at three or more view points free from any spatial positional restriction, and projective transformation matrixes for projecting the images respectively onto predetermined virtual planes are calculated. Then internal parameters of the base camera are calculated on the basis of the projective transformation matrixes relative to the images obtained from the base camera. Subsequently the position of the shot plane is presumed on the basis of the internal parameter of the base camera and the images obtained therefrom, whereby projection matrixes for the detection camera are calculated on the basis of the plane position parameters and the images obtained from the detection camera. According to this device, simplified calibration can be achieved stably without the necessity of any exclusive appliance.
摘要:
The present invention relates to a high-performance camera calibration apparatus and method capable of accomplishing stable high-accuracy parameter estimation. A pattern whose geometrical configuration is known in advance is photographed by a camera to generate a picked-up image, with the generated picked-up image being temporarily stored as an image input in a frame buffer. In addition, a base image having a pattern univocally corresponding in geometrical configuration definition to the picked-up image is generated according to the CG technology or the like, and is stored in another frame buffer. An image registration is made between the base image and the picked-up image to minimize the luminance error, which enables the parameter estimation.
摘要:
An information processing apparatus that compares a query image and a model image and provides support information for discriminating a subject of the model image from a subject of the query image is disclosed. The information processing apparatus includes: a feature point extracting unit extracting one or more feature points from the model image; a feature describing unit describing features of the one or more feature points extracted by the feature point extracting unit; and a discrimination capability value calculating unit generating correlation images among the features described by the feature describing unit, the extracted model image, and one or more other model images for the one or more feature points extracted by the feature point extracting unit, and calculating a discrimination capability value indicating the degree of contribution to discriminating the subject of the model image on the basis of the correlation images.
摘要:
An object recognition device includes: a model image processing unit having a feature point set decision unit setting a feature point set in a model image, and detecting the feature quantity of the feature point set, and a segmentation unit segmenting the model image; a processing-target image processing unit having a feature point setting unit setting a feature point in a processing-target image and detecting the feature quantity of the feature point; a matching unit comparing the feature quantities of the feature points set in the model image and in the processing-target image so as to detect the feature point corresponding to the feature point set, and executes a matching; and a determination unit determining the processing result in the matching unit so as to determine presence/absence of a model object in the processing-target image.
摘要:
An information processing apparatus that compares an input image with a model image to identify the subject of the input image with the subject of the model image. The apparatus includes feature value extraction means for setting feature points, each of which is on an edge of the model image and provided to extract a model image feature value, which is the feature value of the model image, and extracting the model image feature value from each of a plurality of feature value extraction areas in the neighborhood of each of the feature points, and matching means for checking if an input image feature value, which is the feature value of the input image, at the point that is on an edge of the input image and corresponds to the feature point matches any of the plurality of model image feature values at the feature point.