Tencent Technology (shenzhen) Company Limited

Beihang University

Beijing University of Posts and Telecommunications

Beijing University of Aeronautics and Astronautics

Jie Jiang

Guangjun Zhang

Juhong Wang

Tingting Liu

Yue Ming

Qiaoyun Fan

Bo Li

Yong Cheng

Yuhong Liu

Yangyu Tao

Chen Hou

Zhen Wang

Xing Zhang

Fangcheng Fu

Junwei Pan

Gang Guan

Xinguo Wei

Likai Xu

Zhonghai Wu

Xiaoliang Fan

Huanran Xue

Hongzhi Liu

Xuetao Hao

A data processing method includes: acquiring a first intersection set, acquiring a second intersection set, calculating an intersection between the first intersection set and the second intersection set to obtain an intersection result set that includes an intersecting portion of the first intersection data and the second intersection data, and obfuscating the intersection result set to obtain an obfuscation set that includes obfuscated data based on data in the second intersection set and an intersection data set based on the intersection result set.

Data processing method and apparatus, device, and computer-readable storage medium

A method for federated data query includes: using, by a first electronic device, a joint query statement corresponding to a federated data query to obtain at least one operator containing a joint query operator; transforming the joint query operator to a first joint security operator; determining first data for intersection on the first electronic device by executing the first joint security operator, receiving second data for intersection from a second electronic device involved in the federated data query, and performing joint computing on the first data for intersection and the second data for intersection in a form of a ciphertext to obtain a joint data table; and determining a federated data query result corresponding to the at least one operator based on the joint data table.

Method and apparatus for federated data query, electronic device, and computer-readable storage medium

A stellar atmospheric refraction measurement correction method based on collinearity of refraction surfaces, comprising: performing star identification on the basis of observed star vectors in a star sensor and the reference star catalog, to obtain matching relationships between observed stars and reference stars; converting reference star vectors corresponding to the observed stars to a geographic coordinate system before entering the atmosphere to obtain zenith distances and azimuth angles of incident stellar; on the basis of a principle of collinearity of refraction surfaces, performing optimal solving according to imaging coordinates of observation stars, to obtain the optimal position coordinates of the zenith direction on an imaging surface of the star sensor; according to the optimal zenith direction, performing atmospheric refraction correction on all the recognized observed stars by means of the trigonometric cosine formula to obtain corrected star coordinates; and performing optimal solving to obtain the attitude of the star sensor in the geographic coordinate system.

Stellar atmospheric refraction measurement correction method based on collinearity of refraction surfaces

Disclosed in the present disclosure is a representation learning-based star identification method, which utilizes an end-to-end and representation learning based neural network model RPNet, for fast, efficient, and robust full-sky star identification tasks. The RPNet learns a unique star pattern for each star from a huge amount of random simulated star image samples, then a classification is made on these star patterns learned before. The RPNet comprises two parts: (1) a star pattern generator (SPG) based on a star pattern generation network to generate unique star patterns for the star image samples; (2) a star pattern classifier (SPC) to classify the unique star patterns generated on the front end. And a weight search verification algorithm is also proposed in the invention for filtering and verification of main stars of the GRSs identified by the RPNet, which further improves tremendously the identification ability for a single star image.

Representation learning-based star identification method

Aspects of the disclosure provide an information processing apparatus that includes interface circuitry and processing circuitry. The interface circuitry is configured to obtain a text authored by a person. The processing circuitry is configured to analyze the text to obtain measurements of language features of the person, input the measurements of the language features into an evaluation model that is trained to predict a score as a function of the language features, determine a specific score for the person based on the evaluation model and output the specific score of the person for predicting a behavior of the person.

Evaluation method and apparatus based on text analysis, and storage medium

A hand motion identification method includes: obtaining a to-be-identified video; performing area-locating and tracking of a hand for the to-be-identified video, and extracting a red-green-blue (RGB) video and a depth information video of the hand; detecting the RGB video and the depth information video of the hand, to obtain a feature point; representing the feature point by using a 3D Mesh motion scale-invariant feature transform (MoSIFT) feature descriptor; and comparing the 3D Mesh MoSIFT feature descriptor of the feature point with a 3D Mesh MoSIFT feature descriptor in a positive sample obtained through beforehand training, to obtain a hand motion category in the to-be-identified video.

Hand motion identification method and apparatus

The present disclosure provides a three-dimensional facial recognition method and system. The method includes: performing pose estimation on an input binocular vision image pair by using a three-dimensional facial reference model, to obtain a pose parameter and a virtual image pair of the three-dimensional facial reference model with respect to the binocular vision image pair; reconstructing a facial depth image of the binocular vision image pair by using the virtual image pair as prior information; detecting, according to the pose parameter, a local grid scale-invariant feature descriptor corresponding to an interest point in the facial depth image; and generating a recognition result of the binocular vision image pair according to the detected local grid scale-invariant feature descriptor and training data having attached category annotations. The present disclosure can reduce computational costs and required storage space.

Three-dimensional facial recognition method and system

A method for extracting a characteristic of a three-dimensional face image includes: performing face area division, to obtain a group of face areas; projecting each face area onto a corresponding regional bounding sphere; obtaining an indication of the corresponding face area according to the regional bounding sphere, and recording the indication as a regional bounding spherical descriptor of the face area; calculating a weight of the regional bounding spherical descriptor of the face area for each face area; and obtaining a characteristic of a three-dimensional face image according to the indication of the face area and the corresponding weight.

Method and system for extracting characteristic of three-dimensional face image

The disclosure relates to a rapid and high precision centroiding method for spots image comprising the following steps. First, the method requires convoluting the gray value of a pixel with a Gaussian filter and judging whether the result thereof exceeds a predetermined threshold. If the value exceeds the predetermined threshold, the method requires marking the current pixel with a flag to identify which spot it belongs to, and then accumulating the product of the gray value and a coordinate value of the same spot; and at the same time, accumulating the gray value of the same spot; and saving the results of the accumulation respectively. If the gray value of the pixel does not exceed the predetermined threshold, the method requires marking the current pixel as a background flag. After all pixels of the image has been disposed of completely, the method includes calculating a quotient of the accumulations of the product of the gray value and the coordinate value and the accumulations of the gray value, and outputting the quotients. At the same time, a centroiding system for spots image is also presented.

Rapid and high precision centroiding method and system for spots image

A method for calibration of a digital celestial sensor is disclosed. First, an integrated mathematic model for imaging of a celestial sensor is established according to external and internal parameters of the calibration system of the celestial sensor. Second, by rotating two axes of a rotator by different angles, calibration points data are acquired and sent to a processing computer through an interface circuit. Finally, a two-step calibration program is implemented to calculate the calibration parameters by substituting calibration points' data to the integrated mathematic model. An application device of the calibration method is also provided. The device may include a celestial simulator to provide simulated sunlight or starlight, a two-axis rotator to acquire different calibration points' data, and a processing computer to record the calibration points' data and calculate the calibration parameters.

Method and device for calibration of digital celestial sensor

The disclosure relates to a signal processing method for multi aperture sun sensor comprising the following steps: reading the information of sunspots in a row from a centroid coordinate memory, judging the absence of sunspots in that row, identifying the row and column index of the sunspots in the complete row, selecting the corresponding calibration parameter based on the row and column index, calculating attitude with the attitude calculation module the corresponding to identified sunspots, averaging the accumulated attitude of all sunspots and outputting the final attitude. At the same time, a signal processing device for multi aperture sun sensor is also presented. It is comprised of a sunspot absence judgment and an identification module and an attitude calculation module. The disclosure implements the integration of sun sensors without additional image processor or attitude processor, reduces field programmable gate array resource and improves the reliability of sun sensors.

Signal processing method and device for multi aperture sun sensor

The disclosure relates to an APS based integrated sun sensor comprising: a diaphragm unit, a detection unit, a processing electronics unit and an interface unit. The diaphragm unit is operatively connected with the detection unit for forming a sunspots image. The detection unit is configured for outputting a gray value of each pixel. The processing electronics unit is operatively connected with the detector unit and the interface unit respectively, for evaluating an attitude angle on the basis of the gray value and coordinate of each pixel. The interface unit is operatively connected with a host computer, for transferring the attitude angle to the host computer. This disclosure has such merits as high accuracy, wide FOV (Field of View), low power consumption, low weight, small size and high update rate.

Growing community of inventors

Beijing, China

Jie Jiang