Abstract: A rotation speed measurement method based on a femtosecond optical frequency comb is provided. In the method, a rotation axis of a rotating object to be measured and an optical path main axis are coplanar, and perpendicular to each other, and a first converging lens focuses an emitting beam obtained by expanding the laser on a surface of the rotating object. A repetition frequency and a carrier-envelope offset frequency of the femtosecond optical frequency comb are locked during the measurement. A repetition frequency difference is read from a frequency counter. A rotation speed of the rotating object is calculated as follows: M = c ? ? ? f r 4 ? ? ? f r ? sin ? ? ? R = ? ? ? ? f r R .

Abstract: A method and apparatus for recognizing an imaged information-bearing medium, a computer-readable storage device and a computer device are provided. The method comprising: acquiring a first image of the imaged information-bearing medium; performing text recognition on the first image to acquire a text content of the imaged information-bearing medium; classifying the imaged information-bearing medium to acquire a type of the imaged information-bearing medium; and archiving the text content according to the type.

Abstract: A character recognition method includes: performing feature extraction on an image to be recognized to obtain a first feature map; processing the first feature map to at least obtain N first candidate carrier detection boxes, each first candidate carrier detection box being configured to outline a region of a character carrier; screening the N first candidate carrier detection boxes to obtain K first target carrier detection boxes; performing a feature extraction on the first feature map to obtain a second feature map; processing the second feature map to obtain L first candidate character detection boxes, each first candidate character detection box being configured to outline a region containing at least one character; screening the L first candidate character detection boxes to obtain J first target character detection boxes; and recognizing characters in the J first target character detection boxes to obtain J target character informations.

Abstract: The present disclosure provides an answer evaluation method, an answer evaluation system, an electronic device, and a medium. The method comprises: acquiring an answer image, for a test paper answered by a use; classifying the answer image based on a pre-trained test question classification model, so as to obtain an objective question answer area and a subjective question answer area; identifying at least one objective question in the objective question answer area and an objective question answers for each of the at least one objective question; identifying at least one subjective question in the subjective question answer area and a subjective question answers for each of the at least one subjective question; and determining a total score value of the test paper based on the objective question, the objective question answer, the subjective question and the subjective question answer.

Abstract: A gesture control method comprises: acquiring an image; performing a gesture detection on the image to recognize a gesture from the image; determining, if no gesture is recognized from the image, whether a time interval from a last gesture detection, in which a gesture was recognized, to the gesture detection is less than a preset time period; tracking, if the time interval is less than the preset time period, the gesture in the image based on a comparative gesture which is a gesture recognized last time or tracked last time; and updating the comparative gesture with a currently recognized gesture or a currently tracked gesture. A gesture control method is provided that comprises: identifying an image acquisition device for acquiring image, to determine whether the image acquisition device is a depth-of-field image acquisition device, and performing gesture control based on the identification.

Abstract: A three-dimensional reconstruction method includes: acquiring first images captured by a first camera, each of the first images being an image containing a target object; determining a shooting angle of the each of the first images, the shooting angle being configured to characterize a shooting direction relative to the target object when the first camera shoots the first images; determining an angle interval corresponding to the each of the first images from a plurality of angle intervals included in an angle range [0, 360°) based on the shooting angle, and setting the first image as a target image in the angle interval; and three-dimensionally reconstructing the target object based on the target images in the respective angle intervals to obtain a three-dimensional image of the target object.

Abstract: A computer-implemented method of alerting a driver of a vehicle is provided. The computer-implemented method includes obtaining a plurality of consecutive input images during a time interval using a three-dimensional depth camera, a respective one of the plurality of consecutive input images comprising a user sub-image and an object sub-image; deriving three-dimensional coordinates of user feature points in the user sub-image of the respective one of the plurality of consecutive input images using a first classifier; deriving three-dimensional coordinates of object feature points in the object sub-image of the respective one of the plurality of consecutive input images using the first classifier; and classifying user posture in the respective one of the plurality of consecutive input images by analyzing the three-dimensional coordinates of user feature points and the three-dimensional coordinates of object feature points using a second classifier.

Abstract: The present disclosure provides a gesture control method, comprising: A gesture control method, comprising: acquiring an image; performing a gesture detection on the image to recognize a gesture from the image; determining, if no gesture is recognized from the image, whether a time interval from a last gesture detection, in which a gesture was recognized, to the gesture detection is less than a preset time period; tracking, if the time interval is less than the preset time period, the gesture in the image based on a comparative gesture which is a gesture recognized last time or tracked last time; and updating the comparative gesture with a currently recognized gesture or a currently tracked gesture.

Abstract: A translation pen includes: a pen body, an indication component, an image collector and a first processor. The pen body has a pen tip end. The indication component is arranged on the pen tip end. The image collector is arranged on the pen body, and the image collector is configured to: collect an image including a text to be translated according to a position indicated by the indication component, and send the image collected.

Abstract: A character recognition method includes: performing feature extraction on an image to be recognized to obtain a first feature map; processing the first feature map to at least obtain N first candidate carrier detection boxes, each first candidate carrier detection box being configured to outline a region of a character carrier; screening the N first candidate carrier detection boxes to obtain K first target carrier detection boxes; performing a feature extraction on the first feature map to obtain a second feature map; processing the second feature map to obtain L first candidate character detection boxes, each first candidate character detection box being configured to outline a region containing at least one character; screening the L first candidate character detection boxes to obtain J first target character detection boxes; and recognizing characters in the J first target character detection boxes to obtain J target character informations.

Abstract: A method and apparatus for recognizing an imaged information-bearing medium, a computer-readable storage device and a computer device are provided. The method comprising: acquiring a first image of the imaged information-bearing medium; performing text recognition on the first image to acquire a text content of the imaged information-bearing medium; classifying the imaged information-bearing medium to acquire a type of the imaged information-bearing medium; and archiving the text content according to the type.

Abstract: A sample extraction method targeting a video classification problem includes acquiring video data, parsing the video data to obtain a plurality of consecutive single-frame images corresponding to the video data, and extracting feature images from the plurality of consecutive single-frame images to compose samples, where the feature images are used to summarize content information of the video data, and the samples do not contain redundant image data.

Abstract: A three-dimensional reconstruction method includes: acquiring first images captured by a first camera, each of the first images being an image containing a target object; determining a shooting angle of the each of the first images, the shooting angle being configured to characterize a shooting direction relative to the target object when the first camera shoots the first images; determining an angle interval corresponding to the each of the first images from a plurality of angle intervals included in an angle range [0, 360°) based on the shooting angle, and setting the first image as a target image in the angle interval; and three-dimensionally reconstructing the target object based on the target images in the respective angle intervals to obtain a three-dimensional image of the target object.

Abstract: A gesture detection method, a gesture processing device, and a computer readable storage medium. The gesture detection method includes: performing a shrinking process and a background modeling on a first frame of original image, to generate a first frame of background image; determining a motion region of the first frame of background image based on the first frame of background image; determining a first gesture detection area in the first frame of original image according to the motion region of the first frame of background image; and performing a gesture detection within the first gesture detection area.

Abstract: A computer-implemented method of alerting a driver of a vehicle is provided. The computer-implemented method includes obtaining a plurality of consecutive input images during a time interval using a three-dimensional depth camera, a respective one of the plurality of consecutive input images comprising a user sub-image and an object sub-image; deriving three-dimensional coordinates of user feature points in the user sub-image of the respective one of the plurality of consecutive input images using a first classifier; deriving three-dimensional coordinates of object feature points in the object sub-image of the respective one of the plurality of consecutive input images using the first classifier; and classifying user posture in the respective one of the plurality of consecutive input images by analyzing the three-dimensional coordinates of user feature points and the three-dimensional coordinates of object feature points using a second classifier.

Abstract: A gesture recognition method includes determining a palm connected domain based on an acquired depth image. The method includes determining a tracking frame corresponding to the palm connected domain. The method includes recognizing a gesture within a region of a to-be-recognized image corresponding to the tracking frame, based on a location of the tracking frame. In this arrangement, a palm connected domain and a tracking frame corresponding to the palm connected domain are acquired, and a gesture is recognized within a region of a to-be-recognized image corresponding to the tracking frame.

Abstract: A gesture recognition method includes determining a palm connected domain based on an acquired depth image. The method includes determining a tracking frame corresponding to the palm connected domain. The method includes recognizing a gesture within a region of a to-be-recognized image corresponding to the tracking frame, based on a location of the tracking frame. In this arrangement, a palm connected domain and a tracking frame corresponding to the palm connected domain are acquired, and a gesture is recognized within a region of a to-be-recognized image corresponding to the tracking frame.

Abstract: A method for video classification includes: extracting an original image and an optical flow image corresponding to a to-be-classified video from the to-be-classified video; inputting the original image to a space-domain convolutional neural network model to obtain a space-domain classification result corresponding to the to-be-classified video; inputting the optical flow image to a time-domain convolutional neural network model to obtain a time-domain classification result corresponding to the to-be-categorized video, wherein the time-domain convolutional neural network model and the space-domain convolutional neural network model are convolutional neural network models of different network architectures; and merging the space-domain classification result and the time-domain classification result to obtain a classification result corresponding to the to-be-classified video.

Abstract: The present disclosure provides an answer evaluation method, an answer evaluation system, an electronic device, and a medium. The method comprises: acquiring an answer image, for a test paper answered by a use; classifying the answer image based on a pre-trained test question classification model, so as to obtain an objective question answer area and a subjective question answer area; identifying at least one objective question in the objective question answer area and an objective question answers for each of the at least one objective question; identifying at least one subjective question in the subjective question answer area and a subjective question answers for each of the at least one subjective question; and determining a total score value of the test paper based on the objective question, the objective question answer, the subjective question and the subjective question answer.

Abstract: A hand detection method, a hand segmentation method, an image detection method and system, a storage medium, and a device are provided. The image detection method includes: determining a first starting point in a connected domain of an image to be detected; determining n farthest extremum points different from the first starting point, wherein an Nth farthest extremum point is a pixel point in the connected domain having a maximum geodesic distance to an Nth starting point, an (N+1)th starting point is the Nth farthest extremum point, and n and N are both positive integers; performing region growing with the n farthest extremum points as initial points respectively, to acquire n regions in the connected domain; judging whether a relationship between a preset feature of each region and a preset feature of the connected domain satisfies a selection condition, to determine an available region satisfying the selection condition.