Abstract: An unmanned aerial vehicle (UAV) includes a vehicle body and a multi-ocular imaging assembly. The multi-ocular imaging assembly includes at least two imaging devices disposed in and fixed to the vehicle body.

Abstract: A hover control method includes obtaining a flight velocity of an unmanned aerial vehicle (UAV), obtaining an image frame as a keyframe in response to that the flight velocity satisfies a preset condition, and controlling hovering of the UAV using the keyframe as a reference object.

Abstract: The present disclosure provides a method and an apparatus for providing information based on artificial intelligence. The method includes: determining a characteristic of interest of the user according to historical access records of the user; and displaying an information card matched with the characteristic of interest in an information displaying interface, the information card including core contents of news matched with the characteristic of interest determined by analyzing news in a database.

Abstract: A method of using an unmanned aerial vehicle (UAV) to guide a target includes receiving, via the UAV, a signal indicative of a target area for guiding the target, determining an indicator based on a location of the UAV and/or a location of the target area while the target is in motion, and performing, via the UAV, an operation in response to the indicator.

Abstract: A system for automatically adjusting a baseline of an imaging system for stereoscopic imaging and methods for making and using same. The imaging system includes a plurality of imaging devices that cooperate via a baseline adjustment mechanism. The imaging devices can acquire images of an object of interest and ascertain an object distance between the stereoscopic imaging system and the object of interest using triangulation. Based on the object distance, the baseline adjustment mechanism automatically adjusts a baseline between any pair of imaging devices. The baseline can be reduced when the object of interest is proximate to the imaging system and can be increased when the object of interest is distal. Once the baseline has been adjusted, one or more extrinsic parameters of the imaging devices are calibrated using a two-step optimization method. The imaging system is suitable for use aboard a mobile platform such as an unmanned aerial vehicle.

Abstract: A method of controlling an unmanned aerial vehicle (UAV) includes receiving an image from one or more vision sensors of the UAV. The image is captured while the UAV is in flight and includes a marker within an environment. The marker has a visual pattern. The method further includes identifying the visual pattern to determine a plurality of instructions encoded in the visual pattern, and controlling, in response to the plurality of instructions, the UAV to perform an action including at least one of adjusting position of a payload, swapping a payload, or capturing an image of a selected subject.

Abstract: Systems and methods are provided for positing an unmanned aerial vehicle (UAV) in an environment. The UAV may be able to identify visual markers and patterns in the environment. The UAV can distinguish between visual markers and other features in the environment. The visual markers can be analyzed with visual sensors to determine the position of the UAV in the environment. The visual markers can encode instructions to the UAV.

Abstract: A news interaction method, apparatus, device and computer storage medium are proposed. The method includes: obtaining input information input by a user upon reading current news content; obtaining parsing information of the input information based on the current news content, where the parsing information includes intent information of the input information; distributing the input information to at least one news interactive service subsystem according to the intent information of the input information, and receiving a return result returned by the at least one news interactive service subsystem; and selecting a display result from the return result according to a preset policy, and providing the display result obtained by selection to the user. The present disclosure may enrich the interaction function of the current news application, satisfy the user's diverse interaction demands, and achieve provision of more diverse return results to the user.

Abstract: An unmanned aerial vehicle (UAV) includes a vehicle body and a multi-ocular imaging assembly. The multi-ocular imaging assembly includes at least two imaging devices disposed in and fixed to the vehicle body.

Abstract: Embodiments of the present disclosure disclose a method for modifying a segmentation model based on artificial intelligence, a device and a storage medium. The method may include: acquiring a model parameter of the segmentation model, and performing a training on a feature vector corresponding to a preset generalized feature of a first training corpus via a neural network so as to acquire a model parameter of the preset generalized feature; performing a word segmentation on the first training corpus according to the model parameter of the segmentation model and the model parameter of the preset generalized feature, so as to acquire a segmentation result; and comparing the segmentation result with the first training corpus according to a preset rule, and modifying the model parameter of the segmentation model and a parameter of the neural network according to a comparison result.

Abstract: Embodiments of the present disclosure disclose a word segmentation method based on artificial intelligence, a server and a storage medium. The word segmentation method may include: acquiring a corpus to be segmented and a segmentation model corresponding to a preset segmentation template; matching the corpus to be segmented with the segmentation model according to a preset matching algorithm, and acquiring a target phrase satisfying a first preset rule in the corpus to be segmented; modifying an emission matrix corresponding to the segmentation model and the corpus to be segmented according to the target phrase; and performing a word segmentation on the corpus to be segmented according to the emission matrix modified, to acquire a first segmentation result.

Abstract: Embodiments of the present disclosure disclose a method and an apparatus for customizing a word segmentation model based on artificial intelligence, a device and a medium. The method includes the followings. A customized segmentation training corpus is acquired. A first preset word segmentation model is rectified with an increment training method or a weight intervention method, based on the customized segmentation training corpus, to obtain a customized word segmentation model corresponding to the customized segmentation training corpus.

Abstract: An imaging control method includes receiving a starting instruction including a flight mode of an unmanned aerial vehicle (“UAV”). The imaging control method also includes controlling the UAV to fly autonomously based on the flight mode. The imaging control method also includes obtaining, in the flight mode, location information of a target object, and obtaining orientation information of the target object relative to the UAV based on the target object recognized from an image captured by an imaging device carried by a gimbal mounted on the UAV. The imaging control method further includes controlling a flight path of the UAV based on the location information and the flight mode, controlling an attitude of the gimbal to render the target object to appear in the image, and controlling the imaging device to record a video in the flight mode, and to transmit video data to a terminal.

Abstract: A method and device for aerial vehicle-based image projection, and an aerial vehicle are provided. The method comprises adjusting a position of the aerial vehicle to a projection-permitted position if an image projection event for the aerial vehicle is detected, triggering a projection module of the aerial vehicle to project an image. Adjusting the position of the aerial vehicle comprises adjusting the position of the aerial vehicle based on an obstacle image captured in a projecting direction of the projection module.

Abstract: A depth map generating method includes obtaining one or more images from each of one or more imaging devices, and processing the one or more images from each of the one or more imaging devices based on calibration parameters for the one or more imaging devices to generate a three-dimensional depth map. The calibration parameters are determined using a plurality of calibration images of a calibration target from each of the one or more imaging devices. The calibration target includes a plurality of features arranged in a repeating pattern and one or more reference markers each uniquely identifiable within each calibration image of the plurality of calibration images. The plurality of calibration images include at least one calibration image capturing less than all of the plurality of features.

Abstract: A system for controlling an unmanned aerial vehicle (UAV) to switch between different flight modes during operation. The system includes one or more processors configured to determine, based on sensor data received from one or more sensors carried by the UAV, a change in environment of the UAV from a first environment type to a second environment type. In response to determining the change in environment, the one or more processors configured to switch a flight mode of the UAV from a first flight mode to a second flight mode, and effect operation of the UAV in accordance with a second set of operating rules for operating in the second environment type.

Abstract: The present disclosure provides a gesture recognition method. The method includes the following steps: acquiring a depth image of a user; determining a point set of a two-dimensional image indicating a palm based on a depth information of the depth image; and, determining a gesture based on the point set.

Abstract: An image processing method includes correcting a target image based on an initial distortion coefficient to obtain a first corrected target image, performing straight-line fitting on a first border line in the first corrected target image to calculate a first distortion metric value and a correction distortion coefficient, correcting the target image based on the correction distortion coefficient to obtain a second corrected target image, removing outlier points on a second border line in the second corrected target image, performing straight-line fitting on the second border line with the outlier points removed to calculate a second distortion metric value, detecting whether a preset correction condition is satisfied based on at least one of the first distortion metric value or the second distortion metric value, and, if the preset correction condition is satisfied, applying the correction distortion coefficient to subsequent image correction to obtain better corrected images.

Abstract: Systems, methods, and devices for calibrating one or more imaging devices are provided. In one aspect, a method comprises: receiving, from each of the one or more imaging devices, a plurality of images of a calibration target comprising a plurality of features and one or more reference markers; determining a spatial relationship between the one or more reference markers in each image of the plurality of images and the one or more reference markers on the calibration target; formulating, based on the spatial relationship, a correspondence between image coordinates of features in each image of the plurality of images and global coordinates for corresponding features on the calibration target; and determining, based on the correspondence, calibration parameters for the one or more imaging devices.

Abstract: A system for controlling an unmanned aerial vehicle (UAV) includes one or more processors configured to receive sensor data from one or more sensors carried by the UAV. The sensor data is indicative of at least a state of the UAV. The one or more processors are further configured to select a flight mode from a plurality of different flight modes based at least in part on the sensor data and effect operation of the UAV in accordance with a set of operating rules associated with the selected flight mode.