Abstract: The present invention discloses a method and system for multicarrier signal tracking based on deep learning and high precision positioning. Using the data characteristics of S-curve, and using S-curve which contains multipath signals as feature data for training deep learning networks under different signal-to-noise ratios. The delay regression results of receiving signal can be directly obtained by the S-curve of real-time receiving signal and the pre-trained network. The motivation of this method is to fully utilize the advantages of deep learning networks in accurately regressing complex problems with a large amount of data, fundamentally solving the impact of multipath signals on the delay estimation of the main path signal in traditional software defined receivers, extracting the corresponding relationship between the delay of main path and S-curve under the influence of different signal-to-noise ratios and different multipath signals.

Abstract: The present invention discloses a method and system for multicarrier signal tracking based on deep learning and high precision positioning. Using the data characteristics of S-curve, and using S-curve which contains multipath signals as feature data for training deep learning networks under different signal-to-noise ratios. The delay regression results of receiving signal can be directly obtained by the S-curve of real-time receiving signal and the pre-trained network. The motivation of this method is to fully utilize the advantages of deep learning networks in accurately regressing complex problems with a large amount of data, fundamentally solving the impact of multipath signals on the delay estimation of the main path signal in traditional software defined receivers, extracting the corresponding relationship between the delay of main path and S-curve under the influence of different signal-to-noise ratios and different multipath signals.

Abstract: Provided are a tour guiding method and apparatus, an electronic device and a storage medium. The method includes receiving a video stream collected by a user in a current location area of a target scenic spot and sent by an application device; determining, based on the collected video stream and prestored three-dimensional point cloud data of the target scenic spot, an augmented-reality-based content resource package corresponding to the current location area, where the augmented-reality-based content resource package includes at least six-degrees-of-freedom attitude data of the application device; and sending the augmented-reality-based content resource package corresponding to the current location area to the application device to enable the application device to provide the augmented-reality-based content resource package corresponding to the front location area for the user.

Abstract: The present disclosure discloses an edge-based three-dimensional tracking and registration method and apparatus for augmented reality, and a storage medium. The method includes: obtaining an initial pose of a three-dimensional object in an image; extracting edgelet features of a contour of the three-dimensional object based on the initial pose; dividing the edgelet features into groups, and performing searching on the image to find a matching point corresponding to respective edgelet feature in each group; and calculating a pose of the three-dimensional object based on matching points found in the groups.

Abstract: A method and apparatus for generating location information, an electronic device, and a computer readable storage medium are provided. The method may include: constructing a corresponding plane equation based on three-dimensional space coordinates of a matching feature pair of a target plane object included in a pair of adjacent image frames having a frame interval less than a preset interval; merging identical plane equations in generated plane equations to obtain a target plane equation, and finally calculating to obtain real corner coordinates of the target plane object, based on corner theoretical coordinates of a graphic box on a plane corresponding to the target plane equation and gravity information of the target plane object.

Abstract: Provided are a tour guiding method and apparatus, an electronic device and a storage medium. The method includes receiving a video stream collected by a user in a current location area of a target scenic spot and sent by an application device; determining, based on the collected video stream and prestored three-dimensional point cloud data of the target scenic spot, an augmented-reality-based content resource package corresponding to the current location area, where the augmented-reality-based content resource package includes at least six-degrees-of-freedom attitude data of the application device; and sending the augmented-reality-based content resource package corresponding to the current location area to the application device to enable the application device to provide the augmented-reality-based content resource package corresponding to the front location area for the user.

Abstract: A method, apparatus, and an electronic device relate to the field of augmented reality and deep learning technologies. The method includes acquiring a first image that includes a first display plane of a target planar object, and mapping the first image, to acquire a second image including a second display plane, wherein the second image is a front view of the target planar object, and the second display plane is acquired through mapping the first display plane into the second image. The method also includes acquiring a first region in the second image, wherein the first region includes a region where the second display plane is located, and the first region is larger than the region where the second display plane is located. The method furthermore includes generating a sample image in accordance with an image of the first region.

Abstract: The disclosure provides a method for indoor localization, a related electronic device and a related storage medium. A first image position of a target feature point of a target object is obtained and an identifier of the target feature point is obtained based on a first indoor image. A 3D spatial position of the target feature point is obtained through retrieval based on the identifier of the target feature point. The 3D spatial position is pre-determined based on a second image position of the target feature point on a second indoor image, a posture of a camera for capturing the second indoor image, and a posture of the target object on the second indoor image. An indoor position of the user is determined based on the first image position of the target feature point and the 3D spatial position of the target feature point.

Abstract: The present disclosure discloses an edge-based three-dimensional tracking and registration method and apparatus for augmented reality, and a storage medium. The method includes: obtaining an initial pose of a three-dimensional object in an image; extracting edgelet features of a contour of the three-dimensional object based on the initial pose; dividing the edgelet features into groups, and performing searching on the image to find a matching point corresponding to respective edgelet feature in each group; and calculating a pose of the three-dimensional object based on matching points found in the groups.

Abstract: The present disclosure provides a method, an apparatus, a device for evaluating image tracking effectiveness and a readable storage medium. The method includes: extracting feature points from a target image according to a predefined algorithm; determining first texture information for the target image according to the feature points; processing the target image according to a predefined processing policy to derive a contrast image, and determining second texture information for the target image according to the contrast image; and rating the target image according to the first texture information and the second texture information. In the solution provide by the present disclosure, the tracking effectiveness for the target image can be known without having to place the target image into any actual product, nor having to wait until the product has been finalized before the target image tracking effectiveness is determined. Moreover, efficiency can be enhanced when evaluating image tracking effectiveness.

Abstract: An object tracking method, device are provided according to the disclosure. The object tracking method includes: acquiring an object image comprising an object; determining a current image with the object from images captured consecutively, according to the object image; calculating a first pose of the object in the current image using a first algorithm, and calculating a second pose of the object in the current image using a second algorithm, wherein the first algorithm has a faster calculating speed than the second algorithm; determining a pose of the object to be the first pose before a calculation of the second pose is completed; and in a case that the calculation of the second pose is completed, calculating a third pose of the object according to the first pose and the second pose; and determining the pose of the object to be the third pose.

Abstract: An image recognition method and device are provided according to the disclosure. The method includes: obtaining a target image, and extracting at least one first visual feature of the target image; obtaining at least one pending image according to the first visual feature of the target image, and extracting a plurality of second visual features of the target image and the plurality of second visual features of the pending image; for each pending image, forming a plurality of visual feature pairs; and removing an unavailable visual feature pair from the plurality of visual feature pairs, to obtain at least one remaining feature pair; and determining an image similar to the target image from the at least one pending image, according to the at least one remaining feature pair.

Abstract: The present disclosure provides a method, an apparatus, a device for evaluating image tracking effectiveness and a readable storage medium. The method includes: extracting feature points from a target image according to a predefined algorithm; determining first texture information for the target image according to the feature points; processing the target image according to a predefined processing policy to derive a contrast image, and determining second texture information for the target image according to the contrast image; and rating the target image according to the first texture information and the second texture information. In the solution provide by the present disclosure, the tracking effectiveness for the target image can be known without having to place the target image into any actual product, nor having to wait until the product has been finalized before the target image tracking effectiveness is determined. Moreover, efficiency can be enhanced when evaluating image tracking effectiveness.

Abstract: An object tracking method, device are provided according to the disclosure. The object tracking method includes: acquiring an object image comprising an object; determining a current image with the object from images captured consecutively, according to the object image; calculating a first pose of the object in the current image using a first algorithm, and calculating a second pose of the object in the current image using a second algorithm, wherein the first algorithm has a faster calculating speed than the second algorithm; determining a pose of the object to be the first pose before a calculation of the second pose is completed; and in a case that the calculation of the second pose is completed, calculating a third pose of the object according to the first pose and the second pose; and determining the pose of the object to be the third pose.

Abstract: An image recognition method and device are provided according to the disclosure. The method includes: obtaining a target image, and extracting at least one first visual feature of the target image; obtaining at least one pending image according to the first visual feature of the target image, and extracting a plurality of second visual features of the target image and the plurality of second visual features of the pending image; for each pending image, forming a plurality of visual feature pairs; and removing an unavailable visual feature pair from the plurality of visual feature pairs, to obtain at least one remaining feature pair; and determining an image similar to the target image from the at least one pending image, according to the at least one remaining feature pair.