Abstract: A method of measuring an internal resistance of a battery cell and a device therefor are provided. A battery management device includes one or more passive balancing circuits provided for each of one or more battery cells, wherein each passive balancing circuit includes a balancing resistor and a switching element for selectively discharging each battery cell through the balancing resistor, and a control unit configured to determine an alternating current internal resistance of a target battery cell that is subject to cell balancing based on a voltage of the target battery cell before and after a target switching element that is the switching element corresponding to the target battery cell is turned on, and determine a direct current internal resistance of the target battery cell based on an amount of change in the voltage of the target battery cell during a time period after a predetermined time elapses from a time point when the target switching element is turned on.

Abstract: Provided are an object verification apparatus and method. The object verification apparatus includes a matching unit performing a plurality of different matching algorithms on a query image and generating a plurality of scores; a score normalization unit normalizing each of the generated scores to be adaptive to the query image; a weight estimation unit estimating weights of the normalized scores based on the respective matching algorithms applied; and a score fusion unit fusing the normalized scores by respectively applying the weights estimated by the weight estimation unit to the normalized scores.

Abstract: A method and apparatus for performing a conversion of a skin color of an input image into a preference color by applying face detection and skin color detection is disclosed. The method includes: detecting a face area from the input image; detecting a skin area from the input image; judging a common area between the face area and the skin area as a face; extracting a skin color from the input image with reference to the skin color in the judged face; and converting the extracted skin color into an image-adaptive skin color.

Abstract: A method, medium, and apparatus with a generated object descriptor using a curvature gabor filter, with complementary object recognition being performed by applying a general gabor filter and a curvature gabor filter having various curvatures, such that the dimension and efficiency of a feature vector can be increased by detecting correlations between features of an object searching for a parameter and its position of an optimal curvature gabor filter through boosting learning, and projecting the extracted features onto a base vector having the highest classification rate.

Abstract: A method and apparatus for detecting a meaningful motion. The method of detecting a meaningful motion includes generating a difference image including a plurality of regions each having a sign according to a motion of an input image from a plurality of input images, and by calculating the amount of motion in the difference image based on the sign of each of the regions of the difference image, detecting a meaningful motion of the input image. According to the method and apparatus, a high detection ratio can be maintained, while a false alarm ratio with regard to meaningless motion can be lowered.

Abstract: Provided is a method and apparatus for summarizing a moving picture of a sports game. The method includes detecting play sections of the moving picture; calculating a degree of importance of each play section; and summarizing the moving picture including each play section using the degree of importance of each play section.

Abstract: A method and apparatus for extracting feature vectors for face recognition and retrieval are provided. An entire Fourier feature vector is generated for an entire face area of a normalized face image using first and second normalized vectors, and a central Fourier feature vector is generated for a central face area of the normalized face image using third and fourth normalized vectors. An entire intensity feature vector is generated for the entire face area, and a local intensity feature vector is generated for a predetermined number of face component-wise areas. An entire composite feature vector is generated by coupling the first and second normalized vectors and the entire intensity feature, and a central composite feature vector is generated by coupling the third and fourth normalized vectors and the local intensity feature vectors.

Abstract: The present invention relates to a system and method for detecting a face that is capable of quickly and correctly deciding whether an input facial image is occluded, regardless of any type of facial image to be inputted. The present invention is characterized in that eigenvectors and weights are extracted from the input facial image using principal component analysis (PCA) and the extracted eigenvectors and weights of the user image are substituted into a occluding-decision algorithm, whereby it can be determined whether the facial image is occluded.

Abstract: An image retrieval method and apparatus using iterative matching are provided. The method comprises: (a) extracting K similar images in order of matching rank by retrieving N reference images stored in an image database through comparison between a query image selected by a user and the reference images; and (b) performing iterative matching for M similar images, which are ranked higher and selected from the K similar images, with a predetermined frequency, and rearranging the matching ranks of the M similar images. According to the method and apparatus, among similar images retrieved by using a query image selected by a user, M similar images that are ranked higher are selected, and by performing iterative matching for the M similar images using the high-ranked similar image, M similar images are rearranged in order of similarity and output. Accordingly, accuracy of the matching can improve greatly and a load to the retrieval engine due to iterative retrieval can be minimized.

Abstract: A face recognition method using artificial neural network and an apparatus thereof are provided. The apparatus comprises an eigenpaxel selection unit which generates eigenpaxels indicating characteristic patterns of a face and selects a predetermined number of eigenpaxels among the generated eigenpaxels; an eigenfiltering unit which filters an input image with the selected eigenpaxels; a predetermined number of neural networks, each of which corresponds to one of the selected eigenpaxels, receives an image signal which is filtered by the corresponding eigenpaxel, and output a face recognition result; and a determination unit which receives the recognition result from each of the neural networks and outputs a final face recognition result of the input image.

Abstract: Provided are an object verification apparatus and method. The object verification apparatus includes a matching unit performing a plurality of different matching algorithms on a query image and generating a plurality of scores; a score normalization unit normalizing each of the generated scores to be adaptive to the query image; a weight estimation unit estimating weights of the normalized scores based on the respective matching algorithms applied; and a score fusion unit fusing the normalized scores by respectively applying the weights estimated by the weight estimation unit to the normalized scores.

Abstract: A method and apparatus for recognizing and searching for a face using 2nd-order independent component analysis (ICA) are provided. The method for describing feature points uses 2nd-order ICA d to describe a facial image space and improve recognition performance in various illumination conditions. According to the method and apparatus, use of pose or illumination invariant face descriptor enables retrieval of human faces and authentication of a specific individual.

Abstract: A scalable face recognition method and apparatus using complementary features. The scalable face recognition apparatus includes a multi-analysis unit which analyzes a plurality of features of an input face image using a plurality of feature analysis techniques separately, compares the features of the input face image with a plurality of features of a reference image; and provides similarities as the results of the comparison, a fusion unit which fuses the similarities, and a determination unit which classifies the input face image according to a result of the fusion performed by the fusion unit.

Abstract: A face recognition method and apparatus. The face recognition apparatus includes a Gabor filter unit which obtains a plurality of response values by applying a plurality of Gabor filters having different properties to a plurality of fiducial points extracted from an input face image, a linear discriminant analysis (LDA) unit which obtains first LDA results by performing LDA on each of a plurality of response value groups into which the response values of the plurality of response values are classified, a similarity calculation unit which calculates similarities between the first LDA results and second LDA results obtained by performing LDA on a face image other than the input face image, and a determination unit which classifies the input face image according to the similarities.

Abstract: A score fusion method and apparatus. The score fusion method includes receiving a plurality of scores respectively obtained by a plurality of classifiers, and fusing the received scores using a likelihood ratio. The score fusion apparatus includes a fusion unit which receives a plurality of scores respectively obtained by a plurality of classifiers and fuses the received scores using a likelihood ratio, and a parameter providing unit which provides the fusion unit with a plurality of parameters needed for fusing the received scores.

Abstract: Methods, mediums and systems recognizing a face by extracting features from a facial image. According to the method recognizing the face, multiple subimages of a query facial image and one or more target facial images are generated, Fourier transforms on the multiple subimages are performed, and Fourier features from the multiple subimages are extracted using the Fourier-transformed multiple subimages. A similarity between the Fourier features of the query facial image and the one or more target facial images is measured, and similarities with respect to a plurality of target facial images are calculated. An image having a maximum similarity to the query facial image from the one or more target facial images is selected.

Abstract: Provided are a face recognition apparatus and method in which a facial image is divided into facial component images. The apparatus includes a component division unit that divides an input facial image into a plurality of facial component images; a face descriptor generating unit that generates face descriptors using a transform matrix corresponding to the respective facial component images, the face descriptors being characteristic vectors; a registered face descriptor database (DB) that stores registered face descriptors; and an authentication unit that authenticates the input facial image by comparing face descriptors for the input facial image input from the face descriptor generating unit with the registered face descriptors and providing predetermined weights corresponding to each facial component to the comparison results of each facial component.

Abstract: To reduce degradation of recognition performance due to eye detection errors during face verification and to overcome a problem in that sufficient data to design an optimum feature classifier cannot be obtained during face registration, a method includes shifting the positions of eyes detected during face registration in predetermined directions by a predetermined distance to generate pairs of new coordinate points of the eyes; normalizing a face image on the basis of each pair of new coordinate points of the eyes; using the results of normalization in teaching a feature classifier, thereby coping with eye detection errors. In addition, two threshold values are used to prevent a database from being updated with a face of an unregistered person and to update the database with a normal client's face image that has been used during the latest face verification.

Abstract: An apparatus for estimating a facial pose. The apparatus includes a pre-processing module that provides feature points of a subject's face of a received image, and a pose-estimation module that computes sizes of a left half plane and a right half plane of the face from the provided feature points, and a lateral rotation angle of the face from the computed sizes.

Abstract: A method and apparatus for performing a conversion of a skin color of an input image into a preference color by applying face detection and skin color detection is disclosed. The method includes: detecting a face area from the input image; detecting a skin area from the input image; judging a common area between the face area and the skin area as a face; extracting a skin color from the input image with reference to the skin color in the judged face; and converting the extracted skin color into an image-adaptive skin color.