Baidu Online Network Technology (beijing) Co., Ltd.

Beijing Baidu Netcom Science and Technology Co., Ltd.

Beijing Baidu Netcom Science Technology Co., Ltd

Zhaoliang Liu

Yongjie Zhang

Sili Chen

Hongwu Zhang

Yuan Lin

Haoxing Wang

Zhaohu Li

Zhihao Wang

Yuhua Dong

Ziwen Qin

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.

Tour guiding method, electronic device and storage medium

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.

Edge-based three-dimensional tracking and registration method and apparatus for augmented reality, and storage medium

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.

Method, apparatus and device for evaluating image tracking effectiveness and readable storage medium

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.

Object tracking method, device, augmented reality system and storage medium

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.

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Beijing, China

Zhaoliang Liu