Technical solutions for video event recognition relate to the fields of knowledge graphs, deep learning and computer vision. A video event graph is constructed, and each event in the video event graph includes: M argument roles of the event and respective arguments of the argument roles, with M being a positive integer greater than one. For a to-be-recognized video, respective arguments of the M argument roles of a to-be-recognized event corresponding to the video are acquired. According to the arguments acquired, an event is selected from the video event graph as a recognized event corresponding to the video.

Provided herein are detection systems and related methods for detecting moving objects in an airspace surrounding the detection system. In an aspect, the moving object is a flying animal and the detection system comprises a first imager and a second imager that determines position of the moving object and for moving objects within a user selected distance from the system the system determines whether the moving object is a flying animal, such as a bird or bat. The systems and methods are compatible with wind turbines to identify avian(s) of interest in airspace around wind turbines and, if necessary, take action to minimize avian strike by a wind turbine blade.

A method is provided for identifying or authenticating an object. The method includes vibrating the object at a plurality of frequencies. The vibrations from the object are sensed at each of the plurality of frequencies using an accelerometer. A vibration profile of the object is generated using the sensed vibrations. The generated vibration profile is then compared to a stored vibration profile. It is determined if the generated vibration profile matches the stored vibration profile. A match indicates that the object has been identified or authenticated. In another embodiment, an object capable of implementing the method is provided. In another embodiment, the object may include a replaceable accessary. In this case, the initial and generated vibration profiles may be created with the replacement accessary attached to the object. A match of the generated and initial vibration profiles indicates that the replaceable accessary is authentic.

Systems and methods analyzing body fluids contain cells including blood, bone marrow, urine, vaginal tissue, epithelial tissue, tumors, semen, and spittle are disclosed. The systems and methods utilize an improved technique for applying a monolayer of cells to a slide and generating a substantially uniform distribution of cells on the slide. Additionally aspects of the invention also relate to systems and method for utilizing multi-color microscopy for improving the quality of images captured by a light receiving device.

The present invention relate generally to signal encoding and decoding. One claim recites a method comprising: obtaining color image data or color video data, the color image data or color video data comprising an encoded signal pattern, the encoded signal pattern aiding detection of an encoded message, the pattern comprising first frequency components and second frequency components, the color image data or color video data comprising first color data and second color data, in which the first color data comprises the first frequency components encoded therein, and the second color data comprises the second frequency components encoded therein; combining the first color data and the second color data, said combining yielding combined color data; utilizing one or more processors or electronic processing circuitry, detecting the encoded signal pattern from the combined color data, said detecting yielding rotation and scale information; and using the rotation and scale information to detect the encoded message from the combined color data. Of course, other combinations and claims are provided too.

A real-time video enhancement method performed at a terminal includes: obtaining an average luminance of a current frame of an image; in accordance with a determination that the average luminance is less than the luminance threshold: obtaining a pixel range of an area of interest of the current frame; determining a local enhancement curve of the current frame according to the pixel range of the area of interest of the current frame; determining a first enhancement curve corresponding to the current frame according to the average luminance of the current frame; determining a second enhancement curve of the current frame according to the local enhancement curve of the current frame and the first enhancement curve of the current frame; and adjusting the current frame according to the second enhancement curve.

The present invention provides a method and device for acquiring a similar human face picture and acquiring information about a human face picture. It mainly relates to the field of Internet technology, and mainly aims to provide the user a similar human face picture including a similar person when a similar picture is provided. The method comprising: acquiring a human face picture specified by a user; conducting human face identification to the human face picture to identify a similar human face picture of the human face picture from human face pictures that have already been collected; and displaying the similar human face picture to the user.

A shelf space allocation management device manages products allocated on shelves in a store by use of an imaging device. The shelf space allocation management device acquires an image including a position assumed to be changed in allocation status of each product on each shelf; it determines whether each product reflected in the image matches one of pre-recorded images, thus executing a product allocation inspection. Herein, the shelf space allocation management device specifies a position at which a person causes any change in the allocation status of each product on each shelf, and therefore it may control the imaging device to capture an image including the position. It is possible to carry out a product allocation inspection for each period determined in advance depending on the type of each product, or it is possible to carry out a product allocation inspection being triggered by a customer purchasing each product.

Face model matrix training method, apparatus, and storage medium are provided. The method includes: obtaining a face image library, the face image library including k groups of face images, and each group of face images including at least one face image of at least one person, k>2, and k being an integer; separately parsing each group of the k groups of face images, and calculating a first matrix and a second matrix according to parsing results, the first matrix being an intra-group covariance matrix of facial features of each group of face images, and the second matrix being an inter-group covariance matrix of facial features of the k groups of face images; and training face model matrices according to the first matrix and the second matrix.

Systems, devices, media, and methods are presented for generating ideograms from a set of images received in an image stream. The systems and methods detect at least a portion of a face within the image and identify a set of facial landmarks within the portion of the face. The systems and methods determine one or more characteristics representing the portion of the face, in response to detecting the portion of the face. Based on the one or more characteristics and the set of facial landmarks, the systems and methods generate a representation of a face. The systems and methods position one or more graphical elements proximate to the graphical model of the face and generate an ideogram from the graphical model and the one or more graphical elements.