Abstract: A method and a system for exacting face features from data of face images have been disclosed. The system may comprise: A first feature extraction unit configured to filter the data of face images into a first plurality of channels of feature maps with a first dimension and down-sample the feature maps into a second dimension of feature maps; a second feature extraction unit configured to filter the second dimension of feature maps into a second plurality of channels of feature maps with a second dimension, and to down-sample the second plurality of channels feature maps into a third dimension of feature maps; and a third feature extraction unit configured to filter the third dimension of feature maps so as to further reduce high responses outside the face region such that reduce intra-identity variances of face images, while maintain discrimination between identities of the face images.

Abstract: Systems and methods using drawings as security information are disclosed. According to an aspect, a computing device may include a touchscreen display configured to receive information for drawing a security picture. Further, the computing device may include a security manager configured to determine one or more characteristics associated with input of the gesture information. The security manager may also be configured to authenticate a user based on the drawn security picture and the one or more characteristics associated with input of the gesture information.

Abstract: A body relationship estimation method and apparatus are disclosed. The method includes obtaining a target picture, calculating a first body relationship feature of two persons according to at least one of first location information of a body part of each person of the two persons in the target picture or second location information of body parts of the two persons, where the first location information is obtained by performing single-person gesture estimation on each person, and the second location information is obtained by performing two-person joint gesture estimation on the two persons when the first location information indicates that the body parts of the two persons overlap, and determining a body relationship between the two persons according to the first body relationship feature.

Abstract: Disclosed are a method and an apparatus for face verification. The apparatus comprises a feature extracting unit configured to extract HIFs (Hidden identity Features) for different regions of faces by using differently trained ConvNets, wherein last hidden layer neuron activations of said ConvNets are considered as the HIFs. The apparatus further comprises a verification unit configured to concatenate the extracted HIFs of each of the faces to form a feature vector, and then compare two of the formed feature vectors to determine if they are from the same identity or not.

Abstract: The present invention provides a method for video matting via sparse and low-rank representation, which firstly selects frames which represent video characteristics in input video as keyframes, then trains a dictionary according to known pixels in the keyframes, next obtains a reconstruction coefficient satisfying the restriction of low-rank, sparse and non-negative according to the dictionary, and sets the non-local relationship matrix between each pixel in the input video according to the reconstruction coefficient, meanwhile sets the Laplace matrix between multiple frames, obtains a video alpha matte of the input video, according to ? values of the known pixels of the input video and ? values of sample points in the dictionary, the non-local relationship matrix and the Laplace matrix; and finally extracts a foreground object in the input video according to the video alpha matte, therefore improving quality of the extracted foreground object.

Abstract: Methods and electronic devices for adjusting an operating frequency of a memory are disclosed. The method includes: transmitting to the memory a first command that instructs the memory to hold the data information in the memory; transmitting to the memory controller a second command that adjusts the first frequency of the memory controller to a second frequency; and transmitting to the memory a third command that instructs the memory to exchange the data information according to the second frequency of the memory controller. According to the disclosure, it is possible to dynamically adjust the frequency of the memory during operation, avoiding the need of the user to turn off and then turn on the electronic device to adjust the frequency of the memory.

Abstract: Disclosed is an apparatus for face verification. The apparatus may comprise a feature extraction unit and a verification unit. In one embodiment, the feature extraction unit comprises a plurality of convolutional feature extraction systems trained with different face training set, wherein each of systems comprises: a plurality of cascaded convolutional, pooling, locally-connected, and fully-connected feature extraction units configured to extract facial features for face verification from face regions of face images; wherein an output unit of the unit cascade, which could be a fully-connected unit in one embodiment of the present application, is connected to at least one of previous convolutional, pooling, locally-connected, or fully-connected units, and is configured to extract facial features (referred to as deep identification-verification features or DeepID2) for face verification from the facial features in the connected units.

Abstract: Disclosed herein are a system and method for verifying face images based on canonical images. The method includes: retrieving, from a plurality of face images of an identity, a face image with a smallest frontal measurement value as a representative image of the identity; determining parameters of an image reconstruction network based on mappings between the retrieved representative image and the plurality of face images of the identity; reconstructing, by the image reconstruction network with the determined parameters, at least two input face images into corresponding canonical images respectively; and comparing the reconstructed canonical images to verify whether they belong to a same identity, where the representative image is a frontal image and the frontal measurement value represents symmetry of each face image and sharpness of the image. Thus, canonical face images can be reconstructed using only 2D information from face images under an arbitrary pose and lighting condition.

Abstract: An image characteristic estimation method and device is presented, where content of the method includes extracting at least two eigenvalues of input image data, and executing the following operations for each extracted eigenvalue, until execution for the extracted eigenvalues is completed. Selecting an eigenvalue, and performing at least two matrix transformations on the eigenvalue using a pre-obtained matrix parameter in order to obtain a first matrix vector corresponding to the eigenvalue; when a first matrix vector corresponding to each extracted eigenvalue is obtained, obtaining second matrix vectors with respect to the at least two extracted eigenvalues using a convolutional network calculation method according to the obtained first matrix vector corresponding to each eigenvalue; and obtaining a status of an image characteristic in the image data by means of estimation according to the second matrix vectors. In this way, accuracy of estimation is effectively improved.

Abstract: The present invention discloses an image correction method for an adjustable virtual reality helmet. The method comprises the steps of: pre-storing in the helmet a corresponding relation table between a configuration parameter and an image correction parameter and an image correction formula of the helmet; acquiring a real-time configuration parameter of the helmet; searching in the corresponding relation table an image correction parameter corresponding to a configuration parameter closest to the real-time configuration parameter; and performing image correction by calling the image correction formula based on a searched image correction parameter. The present invention also provides an image correction system for an adjustable virtual reality helmet. The present invention can provide better image correction effects for an adjustable virtual reality helmet.

Abstract: A visual semantic complex network system and a method for generating the system have been disclosed. The system may comprise a collection device configured to retrieve a plurality of images and a plurality of texts associated with the images in accordance with given query keywords; a semantic concept determination device configured to determine semantic concepts of the retrieved images and retrieved texts for the retrieved images, respectively; a descriptor generation device configured to, from the retrieved images and texts, generate text descriptors and visual descriptors for the determined semantic concepts; and a semantic correlation device configured to determine semantic correlations and visual correlations from the generated text and visual descriptor, respectively, and to combine the determined semantic correlations and the determined visual correlations to generate the visual semantic complex network system.

Abstract: The present invention discloses a system and method for synthesizing a portrait sketch from a photo. The method includes: dividing the photo into a set of photo patches; determining first matching information between each of the photo patches and training photo patches pre-divided from a set of training photos; determining second matching information between each of the photo patches and training sketch patches pre-divided from a set of training sketches; determining a shape prior for the portrait sketch to be synthesized; determining a set of matched training sketch patches for each of the photo patches based on the first and the second matching information and the shape prior; and synthesizing the portrait sketch from the determined matched training sketch patches.

Abstract: A method and a system for exacting face features from data of face images have been disclosed. The system may comprise: A first feature extraction unit configured to filter the data of face images into a first plurality of channels of feature maps with a first dimension and down-sample the feature maps into a second dimension of feature maps; a second feature extraction unit configured to filter the second dimension of feature maps into a second plurality of channels of feature maps with a second dimension, and to down-sample the second plurality of channels feature maps into a third dimension of feature maps; and a third feature extraction unit configured to filter the third dimension of feature maps so as to further reduce high responses outside the face region such that reduce intra-identity variances of face images, while maintain discrimination between identities of the face images.

Abstract: A method for face image recognition is disclosed. The method comprises generating one or more face region pairs of face images to be compared and recognized; forming a plurality of feature modes by exchanging the two face regions of each face region pair and horizontally flipping each face region of each face region pair; receiving, by one or more convolutional neural networks, the plurality of feature modes, each of which forms a plurality of input maps in the convolutional neural network; extracting, by the one or more convolutional neural networks, relational features from the input maps, which reflect identity similarities of the face images; and recognizing whether the compared face images belong to the same identity based on the extracted relational features of the face images. In addition, a system for face image recognition is also disclosed.

Abstract: A method for face image recognition is disclosed. The method comprises generating one or more face region pairs of face images to be compared and recognized; forming a plurality of feature modes by exchanging the two face regions of each face region pair and horizontally flipping each face region of each face region pair; receiving, by one or more convolutional neural networks, the plurality of feature modes, each of which forms a plurality of input maps in the convolutional neural network; extracting, by the one or more convolutional neural networks, relational features from the input maps, which reflect identity similarities of the face images; and recognizing whether the compared face images belong to the same identity based on the extracted relational features of the face images. In addition, a system for face image recognition is also disclosed.

Abstract: There is disclosed a method and system for use in managing a data storage system. A management system stores information in connection with a data storage system. The information comprises a location of the data storage system. A near field communication link is established between a wireless mobile communications device and the management system in response to the wireless mobile communications device being positioned substantially adjacent the management system. The location of the data storage system is transmitted from the management system to the wireless mobile communications device over the near field communication link. The transmitted location of the data storage system is received in the wireless mobile communications device such that the wireless mobile communications device can assist in locating the data storage system.

Abstract: Techniques are described for utilizing proxy data storage system monitoring aggregators, which are able to keep in synchronization with a central data storage system monitoring aggregator to provide distributed access to the aggregated state and performance monitoring data of all of the data storage arrays.

Abstract: The present disclosure relates to an image re-ranking method, which includes: performing image searching by using an initial keyword, obtaining, by calculation, an anchor concept set of a search result according to the search result corresponding to the initial keyword, obtaining, by calculation, a weight of a correlation between anchor concepts in the anchor concept set, and forming an anchor concept graph ACG by using the anchor concepts in the anchor concept set as vertexes and the weight of the correlation between anchor concepts as a weight of a side between the vertexes; acquiring a positive training sample by using the anchor concepts, and training a classifier by using the positive training sample; obtaining a concept projection vector by using the ACG and the classifier; calculating an ACG distance between images in the search result corresponding to the initial keyword; and ranking the images according to the ACG distance.

Abstract: An automatic technique for a timely diagnostic uses a cloud service and includes (1) after a memory dump file is generated, uploading the dump file and system configurations to an analysis server, (2) extracting key call stacks from the dump file in the server, (3) searching a cloud-based knowledge base for entries corresponding to contents of the call stack and the system configurations (like model, SW version, etc.), these entries representing known issues having similar call stack contents and/or system configurations. If relevant knowledge base entries are found, then they are used to identify a root cause and suggest solutions. If no relevant knowledge base entries are found, this result is reported along with any other potentially useful data from the dump file analysis, such as an identification of a product area for a program identified by the dump file name.

Abstract: A reticle shape regulation device includes: an adsorption device having an upper surface and a lower surface; and a limit mechanism having a limit surface. The adsorption device is movable relative to the limit mechanism at least in a vertical direction. The upper surface of the adsorption device faces toward and is engagable with the limit surface. The lower surface of the adsorption device defines a vacuum chamber that is configured for communication with a negative-pressure source so as to adsorb the reticle by a negative pressure. The lower surface of the adsorption device further defines at least one positive-pressure outlet that is in communication with a positive-pressure source and is configured to supply a continuous positive-pressure air flow between the lower surface of the adsorption device and the reticle during the adsorption of the reticle.