The invention discloses a people searching method and system based on face and human body identification; the method selects an identification mode from two identification modes through sharpness determinations, thus providing options for the identification modes, and effectively improving the identification performance; the method uses a human body identification mode to carry out after-detection tracking, thus preventing face identification failure caused by an unclear face, realizing face detection and tracking of a target person, improving the city safety level without changing hardware, and saving modification costs; the method uses the human body identification to realize ID authentication and behavior monitoring, thus reducing ID authentication and monitoring failure probability, and improving post-event tracing back capability; the searching system comprises a data determination unit, a mode selection unit, and a human body identification unit; the human body identification unit also comprises a face obtaining module and a behavior detection module; beneficial effects of the method and system are realized

People searching method and system based on face and human body identification

The embodiments of the present invention provide a face recognition system and method. The system is deployed on a cloud platform. The system includes a load balancing server, an application service cluster and a face recognition cluster; the load balancing server is used for selecting a target application server, sending an obtained target face recognition request to the target application server and receiving a result acquisition request sent by the target application server; a target face recognition server is selected, and the result acquisition request is forwarded to the target face recognition server; the target application server is used for receiving the target face recognition request, obtaining information to be identified according to information to be processed carried in the target face recognition request; the result acquisition request is sent to the load balancing server; the target face recognition server is used for receiving the result acquisition request forwarded by the load balancing server; face recognition is performed on a source image; and a face recognition result is sent to the initiator of the result acquisition request. With the face recognition system and method provided by the embodiments of the present invention adopted, face recognition efficiency is improved.

Face recognition system and method

The invention belongs to the field of image recognition, and specifically provides a mobile terminal face recognition method and system based on the technology of embedded deep learning. The invention aims at solving problems in the prior art that a human face recognition program is complex, an occupied memory is large, the recognition speed is small, the recognition precision is low and a hand-held mobile terminal for human face recognition is limited by a network signal. In order to solve the above problems, the system comprises a human face detection module for obtaining a face region of a target person; a feature extraction module which is used for obtaining the face features of the target person according to the obtained face region; and a feature comparison module which is used for calculating the similarity between the obtained face features of the target person and preset face features, wherein the human face detection module, the feature extraction module and the feature comparison module are disposed on a mobile terminal. Therefore, the system enables the mobile terminal to be able to judge the identity of the target person quickly and accurately under the condition that there is no network signal.

Mobile terminal face recognition method and system based on technology of embedded deep learning

The invention relates to the technical field of information collection, and provides a statistical method and apparatus of personal information, terminal equipment and a storage medium. The statistical method of personal information includes the steps: according to the first frequency, acquiring the target image in a preset area in real time; detecting whether a face image exists in the target image; if detecting that the face image exists in the target image, acquiring one frame of the target image every first duration until the face image cannot be detected in the target image; performing face identification on the acquired face image in the each frame of target image, and determining the personal identity corresponding to the face image in each frame of the target image; and respectively accumulating the statistical number corresponding to determined different personal identity for one time. If the statistical method of personal information is applied to statistics of the patronagenumber of customers, the statistical method of personal information can solve the problem that the acquired dynamic face images are incorrectly identified as multiple patronage of the same customer, so as to improve the accuracy of statistics of the patronage number of customers.

Statistical method and apparatus of personal information, terminal equipment and storage medium

The invention provides a method for automatically completing codes on the basis of LSTM (Long Short Term Memory). The method comprises the following steps: performing source code processing, and analyzing source codes by using an abstract grammar tree; performing off-line training, and training a language model by using an LSTM model; performing on-line code completion, and completing codes according to the trained language model. The LSTM model comprises constraint character level LSTM and mark character level LSTM with former context marking character encodes. By adopting the method, automatic code completion can be achieved by inputting any character into any place in the encoding process, recommendation of any code can be also achieved, and the recommendation process accuracy can be also ensured. The technical scheme of the invention has the characteristics of being simple and rapid, and the code recommendation accuracy and the recommendation efficiency can be relatively well improved.

Method for automatically completing code on basis of LSTM (Long Short Term Memory)

The invention relates to a face recognition system and method The system at least comprises a data input module, a face analysis module and a data output module; the data input module provides an image sequence to be detected for the face analysis module; with the help of a deep learning technology, the face analysis module performs face recognition, obtains similar faces through a KD tree, performs parallel retrieval, comparison and analysis based on a plurality of sub-databases, and combines analysis results; and the data output module overlaps a face detection frame, face relevant statistical information and original videos and outputs to the front end to display The invention further provides a method for realizing the system The system disclosed by the invention has the characteristics of being automatic, rapid and precise while recognizing faces

The invention relates to an intelligent face tracking system and method based on depth learning and large-scale clustering. The system comprises a video input unit, a distribution server, a face identification server cluster, a streaming media server, a distributed file server, a message center server, a web front server and a client of a common operation system. According to the invention, by use of large-scale cluster servers, based on depth learning based face identification technology, a quite high identification rate can still be maintained under the condition of degraded image quality, and more important, a quite low false alarm rate and a quite low missed examination rate are maintained in a large-scale database, such that the reliability and the robustness of the intelligent tracking system can be ensured, and the intelligent tracking system based on face identification can be really applied to the field of safety protection.

Intelligent face tracking system and method based on depth learning and large-scale clustering

The invention provides a data synchronization method and a data synchronization system. The data synchronization method comprises steps: a network server receives a first data packet sent by a user terminal, wherein the first data packet comprises image data; the network server carries out data processing according to the image data and updates a state identifier according to the data processing result, wherein the state identifier is used for showing the synchronization state of the image data at a network end currently; and when the network server confirms that the data synchronization process is over, the network server sends a first data feedback packet to the user terminal, wherein the first data feedback packet comprises a state identifier. The technical scheme provided by the invention can effectively solve the data synchronization problem in an image retrieval system.

Data synchronization method and data synchronization system

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Face recognition system and method

Intelligent face tracking system and method based on depth learning and large-scale clustering

Data synchronization method and data synchronization system