Abstract: A biometric-based authentication method, an apparatus, and a system are described. The method includes: receiving a biometric image to be authenticated sent from a client; performing feature extraction to the biometric image to be authenticated to obtain a biometric template to be authenticated; comparing the biometric template to be authenticated with a locally-stored biometric template; and returning an authentication result. In this case, the feature extraction process may be implemented at a cloud server side, as such, the complexity of the client may be reduced, the expandability of the client may be increased, a limitation that the biometric recognition may only be implemented on the client may be eliminated, and diversified utilization may be supported.

Abstract: A method and an apparatus for image identification are provided. For example, the processing circuitry of the apparatus obtains first feature values of a first image feature for pixels in an image for barcode detection. The processing circuitry calculates measures that are indicative of changes of the first feature values in multiple directions within the image and determines a target area in the image for the barcode detection according to the measures. Further, the processing circuitry divides the target area into a plurality of sub-areas, and filters the sub-areas to determine a target sub-area for the barcode detection. Then, the processing circuitry obtains second feature values of a second image feature for the target sub-area. The second image feature is derived from the first image feature. The processing circuitry then identifies a barcode type in the target sub-area according to the second image feature.

Abstract: Embodiments of the present application disclose a data pushing method performed at a server. The server obtains a plurality of pieces of theme data that is to be selected when target push data is pushed, the theme data being used for displaying different theme pages of the target push data; selects, from the theme data, target theme data that is used when the target push data is pushed; and pushes the target push data to a second client and causes displaying, on a first client, a first target theme page that is obtained after the target push data is pushed when a first instruction of the first client is received to push the target push data to the second client, and causes displaying a second target theme page corresponding to the first target theme page on the second client after the second client receives the target push data.

Abstract: Systems and methods are provided for facial property identification. For example, an image sample is acquired; a first effective area image of a face is acquired in the image sample; first textural features of the first effective area image are extracted; and the first textural features of the first effective area image are classified by race, gender and age using a race classifier, a gender classifier and an age classifier successively to obtain a race property, a gender property and an age property of the face.

Abstract: A biometric-based authentication method, an apparatus, and a system are described. The method includes: receiving a biometric image to be authenticated sent from a client; performing feature extraction to the biometric image to be authenticated to obtain a biometric template to be authenticated; comparing the biometric template to be authenticated with a locally-stored biometric template; and returning an authentication result. In this case, the feature extraction process may be implemented at a cloud server side, as such, the complexity of the client may be reduced, the expandability of the client may be increased, a limitation that the biometric recognition may only be implemented on the client may be eliminated, and diversified utilization may be supported.

Abstract: A method and an apparatus for image identification are provided. For example, the processing circuitry of the apparatus obtains first feature values of a first image feature for pixels in an image for barcode detection. The processing circuitry calculates measures that are indicative of changes of the first feature values in multiple directions within the image and determines a target area in the image for the barcode detection according to the measures. Further, the processing circuitry divides the target area into a plurality of sub-areas, and filters the sub-areas to determine a target sub-area for the barcode detection. Then, the processing circuitry obtains second feature values of a second image feature for the target sub-area. The second image feature is derived from the first image feature. The processing circuitry then identifies a barcode type in the target sub-area according to the second image feature.

Abstract: A biometric-based authentication method, an apparatus, and a system are described. The method includes: receiving a biometric image to be authenticated sent from a client; performing feature extraction to the biometric image to be authenticated to obtain a biometric template to be authenticated; comparing the biometric template to be authenticated with a locally-stored biometric template; and returning an authentication result. In this case, the feature extraction process may be implemented at a cloud server side, as such, the complexity of the client may be reduced, the expandability of the client may be increased, a limitation that the biometric recognition may only be implemented on the client may be eliminated, and diversified utilization may be supported.

Abstract: Systems and methods are provided for facial property identification. For example, an image sample is acquired; a first effective area image of a face is acquired in the image sample; first textural features of the first effective area image are extracted; and the first textural features of the first effective area image are classified by race, gender and age using a race classifier, a gender classifier and an age classifier successively to obtain a race property, a gender property and an age property of the face.

Abstract: In the present disclosure, a client feature and a pre-stored template image feature are obtained; the obtained client feature and template image feature are projected according to a preset projection matrix, to generate a projection feature pair, where the projection matrix is formed by training of a first template image feature of a same object and a second template image feature of a different object; and similarity calculation is performed on the projection feature pair according to a preset similarity calculation rule, to generate a similarity result and prompt the similarity result to a client.

Abstract: Systems and methods are provided for facial property identification. For example, an image sample is acquired; a first effective area image of a face is acquired in the image sample; first textural features of the first effective area image are extracted; and the first textural features of the first effective area image are classified by race, gender and age using a race classifier, a gender classifier and an age classifier successively to obtain a race property, a gender property and an age property of the face.

Abstract: Systems and methods are provided for acquiring classification functions for facial age identification. For example, a plurality of facial images associated with different ages are acquired; the facial images are assigned into a plurality of facial image collections based on at least information associated with a plurality of first age groups; for a first age group, one or more first facial image collections associated with one or more second age groups older than the first age group are acquired as positive samples; one or more second facial image collections associated with one or more third age groups younger than the first age group are acquired as negative samples; and training is performed based on at least information associated with the first positive samples and the negative samples to determine one or more classification functions for the first age groups.

Abstract: Disclosed is a friend recommendation method, comprising: creating a recommendation backlist for a user; deleting a recommended object included in the recommendation backlist of the user from a recommended object list; and recommending remaining recommended objects in the recommended object list to the user. The present application further discloses a server and a storage medium, so as to recommend friends based on the requirements of a user and recommend objects that the user is really interested in. Therefore, the accuracy and efficiency of friend recommendation are improved, friends can be recommended effectively and the user experience is enhanced.

Abstract: A method for real face image recognition may include obtaining, by at least one processor, an human face image from an original image; obtaining, by at least one processor, a first image by executing a Point Divid Arithmetic Mean Illumination Treatment on the human face image; executing, by at least one processor, a Fourier transformation on the first image and obtaining, by at least one processor, the transformed value of each pixel of the first image; determining, by at least one processor, whether the human face image is a real human face according to the transformed value of each pixel of the first image and the preset classification threshold.

Abstract: A method, system and computer storage medium for visual searching based on cloud service is disclosed. The method includes: receiving, from a client, an image recognition request of cloud service, the request containing image data; forwarding, according to a set classified forwarding rule, the image data to a corresponding classified visual search service; recognizing, by the respective corresponding classified visual search services, corresponding classified type information in the image data, and determining a corresponding name of the image data in accordance with the respective classified type information, and obtaining a classified visual search result; summarizing and sending, to a client, the classified visual search result of the corresponding classified visual search service.

Abstract: A method for real face image recognition may include obtaining, by at least one processor, an human face image from an original image; obtaining, by at least one processor, a first image by executing a Point Divid Arithmetic Mean Illumination Treatment on the human face image; executing, by at least one processor, a Fourier transformation on the first image and obtaining, by at least one processor, the transformed value of each pixel of the first image; determining, by at least one processor, whether the human face image is a real human face according to the transformed value of each pixel of the first image and the preset classification threshold.

Abstract: In the present disclosure, a client feature and a pre-stored template image feature are obtained; the obtained client feature and template image feature are projected according to a preset projection matrix, to generate a projection feature pair, where the projection matrix is formed by training of a first template image feature of a same object and a second template image feature of a different object; and similarity calculation is performed on the projection feature pair according to a preset similarity calculation rule, to generate a similarity result and prompt the similarity result to a client.

Abstract: The present invention relates to a method, device and storage medium for locating feature points on a human face. The method for locating feature points on a human face of the present invention comprises: preliminary locating of the position of a human face by combining human face detection with human eye matching, and acquiring preliminary locating information; according to the preliminary locating information, fitting feature points on the human face; and according to the fitting result, completing the locating of the feature points on the human face. The present invention has the beneficial effects that: by using human face detection and human eye matching at the same time, and incorporating at least one feature of an appearance model according to the preliminary locating information, the position information about a human face is more accurately located, and the location of the feature points on the human face is accurately accomplished.

Abstract: Systems for matching face shapes may include a computer-readable non-transitory storage medium and an executing hardware unit. The storage medium may include a set of instructions for target object shape matching. The executing hardware unit may be in communication with the storage medium and may be configured to execute the set of instructions. The executing hardware unit may be configured to obtain a target object image for shape matching; determine a shape character of the target object image based on a shape of the target object image; determine similarities between the target object image and a plurality of template images of reference objects based on the shape character of the target object image and shape characters of the reference objects in the plurality of template images; and select a template image from the plurality of template images that has a largest similarity to the target object image.

Abstract: Provided is a method for maintaining a login state of a user account, including: acquiring a data access request corresponding to a user ID, the data access request includes a session ID corresponding to the user ID; extracting the session ID from the data access request, and acquiring a session corresponding to the session ID; and allocating the session acquired to the data access request. Also provided are a system and a storage medium for a user account to maintain a login state. The aforementioned method, system and storage medium for a user account to maintain a login state can reduce resource overheads.

Abstract: A method, system and computer storage medium for visual searching based on cloud service is disclosed. The method includes: receiving, from a client, an image recognition request of cloud service, the request containing image data; forwarding, according to a set classified forwarding rule, the image data to a corresponding classified visual search service; recognizing, by the respective corresponding classified visual search services, corresponding classified type information in the image data, and determining a corresponding name of the image data in accordance with the respective classified type information, and obtaining a classified visual search result; summarizing and sending, to a client, the classified visual search result of the corresponding classified visual search service.