Abstract:
An apparatus and method for generating synthetic training data for motion recognition. The method includes generating a three-dimensional (3D) human body model in real time according to motion of a human body, converting volume data of the 3D human body model into a 3D linear structure and extracting skeletal joint information, generating a data set of a human body image and skeletal joint information by rendering the 3D human body model and the skeletal joint information, and providing the data set of the image and the skeletal joint information as synthetic training data for motion recognition.
Abstract:
A method of increasing a photographing speed of a photographing device which capture an image through a combination of two or more photographing devices and generate and provide an image by using the captured image, thereby increasing a photographing speed. An RGB image obtaining device and a depth image obtaining device alternately perform photographing to obtain an image. Also, a second depth image and a second RGB image respectively corresponding to a first RGB image and a first depth image which are alternately obtained by performing alternate photographing are synthesized and output, thereby actually increasing a photographing speed by twice.
Abstract:
An apparatus and method for analyzing a golf motion. The apparatus includes acquiring, by an image sensor of a camera unit, a 2D image of motion of a user, acquiring, by a depth sensor of the camera unit, a depth image to temporally alternate with acquisition of the 2D image, the depth image including depth values of pixels in the 2D image, increasing an image-capturing speed by generating a corresponding depth image or a corresponding 2D image, which corresponds to a reference 2D image or a reference depth image acquired at a predetermined time, outputting the reference 2D image and the corresponding depth image or the reference depth image and the corresponding 2D image as output data for motion analysis, extracting skeletal information of the user through analysis of output data, and displaying motion of the user on a display unit based on skeletal information.
Abstract:
A hand motion recognizing apparatus obtains an image with first resolution including a hand and an image with second resolution higher than the first resolution including the hand, maps the image with the first resolution and the image with the second resolution, extracts a hand position from the image with the first resolution, obtains a hand region corresponding to the hand position from the image with the second resolution mapped to the image with the first resolution, and subsequently estimates a hand motion from the hand region.
Abstract:
An image recognition apparatus using a scalable compact local feature descriptor is provided. The image recognition apparatus includes a feature descriptor generator, a database, and a descriptor matcher. The feature descriptor generator extracts scalable compact local feature descriptor information for recognizing an object from input image information. The database includes information on a plurality of feature descriptors. The descriptor matcher compares a feature descriptor output from the feature descriptor generator with a plurality of feature descriptors stored in the database to recognize an object included in an image.