Abstract:
The size of a feature descriptor is reduced with the accuracy of object identification maintained. A local feature descriptor extracting apparatus includes a feature point detecting unit configured to detect feature points in an image, a local region acquiring unit configured to acquire a local region for each of the feature points, a subregion dividing unit configured to divide each local region into a plurality of subregions, a subregion feature vector generating unit configured to generate a feature vector with a plurality of dimensions for each of the subregions in each local region, and a dimension selecting unit configured to select dimensions from the feature vector in each subregion so as to reduce a correlation between the feature vectors in proximate subregions based on positional relations among the subregions in each local region and output elements of the selected dimensions as a feature descriptor of the local region.
Abstract:
A POS terminal device capable of improving a recognition rate in a process for recognizing a commodity irrespective of the surrounding environment is provided. A POS terminal device (1) includes a brightness measurement unit (2), an irradiation unit (4), an image pickup unit (6), and a recognition process unit (8). The brightness measurement unit (2) measures the brightness of environmental light around the POS terminal device (1). The irradiation unit (4) irradiates a commodity with light, the light being adjusted according to the brightness of the environmental light measured by the brightness measurement unit (2). The image pickup unit (6) shoots the commodity irradiated with the light by the irradiation unit (4) and thereby generates an image thereof. The recognition process unit (8) performs a process for recognizing the commodity based on the image generated by the shooting performed by the image-pickup unit (6).
Abstract:
A search object and m-number of first local features respectively constituted by a feature vector of 1 to i dimensions of local areas of m-number of feature points in an image of the search object are stored, feature points are extracted from the image, second local features respectively constituted by a feature vector of 1 dimension to j dimensions are generated with respect to local areas of n-number of feature points, a smaller number of dimensions among the number of dimensions i of the first local features and the number of dimensions j of the second local features is selected, and an existence of the search object in the image in the video is recognized when a prescribed ratio of the m-number of first local features up to the selected number of dimensions corresponds to the n-number of second local features up to the selected number of dimensions.
Abstract:
A medical article and m-number of first local features which are respectively constituted by a feature vector of 1 dimension to i dimensions of m-number of feature points in an image of the medical article are stored in association with each other, n-number of feature points are extracted from an image in a captured video, n-number of second local features respectively constituted by a feature vector of 1 dimension to j dimensions are generated, a smaller number of dimensions among the number of dimensions i and the number of dimensions j is selected, and an existence of the medical article in the image in the video is recognized when it is determined that a prescribed ratio or more of the m-number of first local features up to the selected number of dimensions corresponds to the n-number of second local features up to the selected number of dimensions.
Abstract:
An object of the present invention is to reduce a size of a feature descriptor while maintaining accuracy of object identification. A local feature descriptor extracting apparatus includes: a feature point detecting unit which detects a plurality of feature points in an image and which outputs feature point information that is information regarding each feature point; a feature point selecting unit which selects a prescribed number of feature points in an order of importance from the plurality of detected feature points, based on the feature point information; a local region acquiring unit which acquires a local region corresponding to each selected feature point; a subregion dividing unit which divides each local region into a plurality of subregions; a subregion feature vector generating unit which generates a feature vector of a plurality of dimensions for each subregion in each local region; and a dimension selecting unit which selects a dimension from the feature vector for each subregion so that a correlation between neighboring subregions is lowered, based on a positional relationship between subregions in each local region and which outputs an element of the selected dimension as a feature descriptor of the local region.