Abstract:
A fingerprint recognition method includes receiving an input partial image corresponding to a partial image of a fingerprint of a first user; partitioning the input partial image into a plurality of blocks; performing a comparison operation based on the plurality of blocks and the enrolled partial images corresponding to partial images of an enrolled fingerprint; and recognizing the fingerprint of the first user based on a result of the comparison operation.
Abstract:
A method for updating biometric authentication data authenticates an input image using an enrollment database (DB) over a first length of time, the authentication including generating information for authenticating the input image, and updates the enrollment DB based on the first length time and the information for authenticating the input image.
Abstract:
A portable device and user input method of the portable device using a virtual input area is provided. The portable device may include a sensor configured to sense a user input to an input area, the input area being at least a portion of an area adjacent to the portable device, a determiner configured to determine a target object corresponding to the user input among at least one input object displayed on the portable device, based on an arrangement of the at least one input object, and a controller configured to generate a control command to control the target object.
Abstract:
At least one example embodiment discloses an image feature extracting method. The method includes determining a probabilistic model based on pixel values of pixels in a kernel, determining image feature information of a current pixel of the pixels in the kernel and determining whether to change the image feature information of the current pixel based on a random value and a probability value of the current pixel, the probability value being based on the probabilistic model.
Abstract:
Provided are a method and apparatus for processing a convolution operation in a neural network, the method includes determining a precision of feature map operands and a precision of weight operands, respectively, on which the convolution operation is to be performed in parallel, decomposing a multiplier included in a convolution operator into sub-multipliers based on the precision of the feature map operands and the precision of the weight operands, performing the convolution operation between the feature map operands and the weight operands by using the decomposed sub-multipliers, each operand being processed in a sub-multiplier corresponding to a precision of the operand, and obtaining output feature maps corresponding to results of the convolution operation.
Abstract:
A processor-implemented method of performing convolution operations in a neural network includes generating a plurality of first sub-bit groups and a plurality of second sub-bit groups, respectively from at least one pixel value of an input feature map and at least one predetermined weight, performing a convolution operation on a first pair that includes a first sub-bit group including a most significant bit (MSB) of the at least one pixel value and a second sub-bit group including an MSB of the at least one predetermined weight, based on the plurality of second sub-bit groups, obtaining a maximum value of a sum of results for convolution operations of remaining pairs excepting the first pair, and based on a result of the convolution operation on the first pair and the maximum value, determining whether to perform the convolution operations of the remaining pairs.
Abstract:
A method for updating biometric authentication data authenticates an input image using an enrollment database (DB) over a first length of time, the authentication including generating information for authenticating the input image, and updates the enrollment DB based on the first length time and the information for authenticating the input image.
Abstract:
A user authentication method using a fingerprint image, the user authentication method includes receiving at least a portion of a fingerprint image of a user; actuating a processor to divide the fingerprint image into a plurality of first sub-blocks; generate a set of input codes by encoding the first sub-blocks based on a coded model; measure a similarity between the set of the input codes and a set of registered codes included in a pre-registered binary codebook; and authenticate the user based on the similarity.
Abstract:
A method and an apparatus for recognizing a touch gesture are disclosed, in which the apparatus may obtain a depth image in which a touch object and a background area are captured, detect a touch input applied by the touch object to the background area in a touch detection area, and recognize a touch gesture associated with the touch input by tracking a change in the touch input.
Abstract:
A method and an apparatus for extracting a facial feature and a method and an apparatus for recognizing a face are provided, in which the apparatus for extracting a facial feature may extract facial landmarks from a current input image, sample a skin region and a facial component region based on the extracted facial landmarks, generate a probabilistic model associated with the sampled skin region and the facial component region, extract the facial component region from a face region included in the input image using the generated probabilistic model, and extract facial feature information from the extracted facial component region.