Abstract: Embodiments of this application disclose a position and attitude determining method. The method includes acquiring, by tracking a feature point of a first marked image, position and attitude parameters of an image captured by a camera; using a previous image of a first image as a second marked image in response to the previous image of the first image meeting a feature point tracking condition and the first image failing to meet the feature point tracking condition; acquiring, position and attitude parameters of the image captured by the camera relative to the second marked image; acquiring position and attitude parameters according to the position and attitude parameters of the image relative to the second marked image and position and attitude parameters of each marked image relative to a previous marked image; and determining a position and an attitude of the camera according to the position and attitude parameters.

Abstract: A relocalization method includes: obtaining, by a front-end program run on a device, a target image acquired after an ith marker image in the plurality of marker images; determining, by the front-end program, the target image as an (i+1)th marker image when the target image satisfies a relocalization condition, and transmitting the target image to a back-end program; performing, by the front-end program, feature point tracking on a current image acquired after the target image relative to the target image to obtain a first pose parameter. The back-end program performs relocalization on the target image to obtain a second pose parameter, and transmits the second pose parameter to the front-end program. The front-end program calculates a current pose parameter of the current image according to the first pose parameter and the second pose parameter.

Abstract: This application discloses a repositioning method performed by an electronic device in a camera pose tracking process, belonging to the field of augmented reality (AR). The method includes: obtaining a current image acquired by the camera after an ith anchor image in a plurality of anchor images; obtaining an initial feature point and an initial pose parameter in a first anchor image in the plurality of anchor images in a case that the current image satisfies a repositioning condition; performing feature point tracking on the current image relative to the first anchor image, to obtain a target feature point; calculating a pose change amount of a camera from a first camera pose to a target camera pose according to the initial feature point and the target feature point; and performing repositioning according to the initial pose parameter and the pose change amount to obtain a target pose parameter.

Abstract: Embodiments of this application disclose a position and pose determining method performed at an electronic device. The method includes: acquiring, by tracking a first feature point extracted from a marked image, position and pose parameters of a first image captured by a camera relative to the marked image; extracting a second feature point from the first image in a case that the first image fails to meet a feature point tracking condition; and acquiring, by tracking the first feature point and the second feature point, position and pose parameters of a second image captured by the camera relative to the marked image, and determining a position and a pose of the camera according to the position and pose parameters, the second image being an image captured by the camera after the first image.

Abstract: This application discloses a repositioning method and apparatus in a camera pose tracking process, a device, and a storage medium, belonging to the field of augmented reality (AR).

Abstract: A depth information determining method for dual cameras is provided. A tth left eye matching similarity from a left eye image captured by a first camera of the dual cameras to a right eye image captured by a second camera of the dual cameras is obtained. A tth right eye matching similarity from the right eye image to the left eye image is obtained. The tth left eye matching similarity and a (t?1)th left eye attention map are processed with a neural network model, to obtain a tth left eye disparity map. The tth right eye matching similarity and a (t?1)th right eye attention map are processed with the neural network model, to obtain a tth right eye disparity map. First depth information is determined according to the tth left eye disparity map. Second depth information is determined according to the tth right eye disparity map.

Abstract: This application discloses a repositioning method performed by an electronic device in a camera pose tracking process, belonging to the field of augmented reality (AR). The method includes: obtaining a current image acquired by the camera after an ith anchor image in a plurality of anchor images; selecting a target keyframe from a keyframe database according to Hash index information in a case that the current image satisfies a repositioning condition; performing second repositioning on the current image relative to the target keyframe; and calculating a camera pose parameter of a camera during acquisition of the current image according to a positioning result of the first repositioning and a positioning result of the second repositioning. In a case that there are different keyframes covering a surrounding area of a camera acquisition scene, it is highly probable that repositioning can succeed, thereby improving the success probability of a repositioning process.

Abstract: A method for controlling an unmanned aerial vehicle (UAV) includes receiving first sensor data relative to a first coordinate system and second sensor data relative to a second coordinate system from a first sensor and a second sensor, respectively. The first and second sensor data includes first and second obstacle occupancy information indicative of relative locations of a first and a second sets of obstacles in reference to the UAV in the first and second coordinate systems, respectively. The first and second sets of obstacles have at least a subset of obstacles in common. The method further includes converting the first and second sensor data into a single coordinate system using sensor calibration data to generate an obstacle occupancy grid map based on the first and second obstacle occupancy information, and effecting the UAV to navigate using the obstacle occupancy grid map to perform obstacle avoidance.

Abstract: Systems, methods, and devices are provided for controlling a movable object using multiple sensors. In one aspect, a method for calibrating one or more extrinsic parameters of a movable object having a plurality of sensors in an initial configuration is provided. The method can comprise: detecting that the initial configuration of the plurality of sensors has been modified; receiving inertial data from at least one inertial sensor during operation of the movable object; receiving image data from at least two image sensors during the operation of the movable object; and estimating the one or more extrinsic parameters based on the inertial data and the image data in response to detecting that the initial configuration has been modified, wherein the one or more extrinsic parameters comprise spatial relationships between the plurality of sensors in the modified configuration.

Abstract: A method includes obtaining previous state information of a movable object, receiving inertial data from at least one inertial sensor carried by the movable object, receiving image data from at least two image sensors carried by the movable object, and estimating updated state information of the movable object based on at least one of the previous state information, the inertial data, or the image data.

Abstract: Systems and methods for controlling a movable object within an environment are provided. In one aspect, a method may comprise: determining, using at least one of a plurality of sensors carried by the movable object, an initial location of the movable object; generating a first signal to cause the movable object to navigate within the environment; receiving, using the at least one of the plurality of sensors, sensing data pertaining to the environment; generating, based on the sensing data, an environmental map representative of at least a portion of the environment; receiving an instruction to return to the initial location; and generating a second signal to cause the movable object to return to the initial location, based on the environmental map.

Abstract: Systems, methods, and devices are provided for controlling a movable object using multiple sensors. In one aspect, a method for calibrating one or more extrinsic parameters of a movable object having a plurality of sensors in an initial configuration is provided. The method can comprise: detecting that the initial configuration of the plurality of sensors has been modified; receiving inertial data from at least one inertial sensor during operation of the movable object; receiving image data from at least two image sensors during the operation of the movable object; and estimating the one or more extrinsic parameters based on the inertial data and the image data in response to detecting that the initial configuration has been modified, wherein the one or more extrinsic parameters comprise spatial relationships between the plurality of sensors in the modified configuration.

Abstract: Systems, methods, and devices are provided for controlling a movable object using multiple sensors. In one aspect, a method for calibrating one or more extrinsic parameters of a movable object having a plurality of sensors in an initial configuration is provided. The method can comprise: detecting that the initial configuration of the plurality of sensors has been modified; receiving inertial data from at least one inertial sensor during operation of the movable object; receiving image data from at least two image sensors during the operation of the movable object; and estimating the one or more extrinsic parameters based on the inertial data and the image data in response to detecting that the initial configuration has been modified, wherein the one or more extrinsic parameters comprise spatial relationships between the plurality of sensors in the modified configuration.

Abstract: Systems and methods for controlling a movable object within an environment are provided. In one aspect, a method may comprise: determining, using at least one of a plurality of sensors carried by the movable object, an initial location of the movable object; generating a first signal to cause the movable object to navigate within the environment; receiving, using the at least one of the plurality of sensors, sensing data pertaining to the environment; generating, based on the sensing data, an environmental map representative of at least a portion of the environment; receiving an instruction to return to the initial location; and generating a second signal to cause the movable object to return to the initial location, based on the environmental map.