Abstract:
An electronic device is disclosed. The electronic device may comprise: an image sensor for acquiring raw image data corresponding to light of infrared band and visible light band, with respect to an external object; and a processor, wherein the processor is configured to: receive a request for acquiring the raw image data corresponding to the external object; on the basis of the request configured to be performed using a first function of the image sensor, generate an RGB image related to the external object by using first raw image data corresponding to the light of visible light band, obtained through the image sensor, and on the basis of the request configured to be performed using a second function of the image sensor, perform biometric authentication related to the external object by using second raw image data corresponding to the light of infrared band, obtained through the image sensor. In addition, various embodiments recognized through the specification are possible.
Abstract:
A transmitter configured to support a multimode and a multiband, using radio frequency (RF) digital-to-analog converters (DACs), includes a first RF DAC configured to transmit a first signal in a first frequency band, and a second RF DAC configured to transmit a second signal in a second frequency band different from the first frequency band. The transmitter further includes an impedance controller configured to adjust impedance of one of the first RF DAC and the second RF DAC operating in an impedance matching mode to adjust a frequency range of another one of the first RF DAC and the second RF DAC operating in a data transmission mode.
Abstract:
An image processing apparatus and method may accurately separate only humans among moving objects, and also accurately separate even humans who have no motion via human segmentation using a depth data and face detection technology. The apparatus includes a face detecting unit to detect a human face in an input color image, a background model producing/updating unit to produce a background model using a depth data of an input first frame and face detection results, a candidate region extracting unit to produce a candidate region as a human body region by comparing the background model with a depth data of an input second or subsequent frame, and to extract a final candidate region by removing a region containing a moving object other than a human from the candidate region, and a human body region extracting unit to extract the human body region from the candidate region.
Abstract:
An image processing apparatus for searching for a feature point by use of a depth image and a method thereof are provided. The image processing apparatus includes an input unit configured to input a three-dimensional image having depth information, a feature point extraction unit configured to obtain a designated point from an object image extracted from the depth image to obtain a feature point that is located at a substantially farthest distance from the designated point, and to obtain other feature points that are located at substantially farthest distances from feature points that are previously obtained as well as the designated point. The apparatus includes a control unit configured to control the input unit and the feature point extraction unit so that time in estimating a structure of the object is reduced, and a recognition result is enhanced.
Abstract:
An apparatus and a method for pose recognition, the method for pose recognition including generating a model of a human body in a virtual space, predicting a next pose of the model of the human body based on a state vector having an angle and an angular velocity of each part of the human body as a state variable, predicting a depth image about the predicted pose, and recognizing a pose of a human in a depth image captured in practice, based on a similarity between the predicted depth image and the depth image captured in practice, wherein the next pose is predicted based on the state vector having an angular velocity as a state variable, thereby reducing the number of pose samples to be generated and improving the pose recognition speed.