Boe Technology Group Co., Ltd.

Beijing Boe Technology Development Co., Ltd.

Boe Technology Groupco., Ltd.

Apollo Intelligent Driving Technology (beijing) Co., Ltd.

Xiangyang Liu

Tong Liu

Xiaojun Tang

Naifu Wu

Zhiguo Zhang

Xitong Ma

Hui Rao

Li Wang

Lihua Geng

Bo Xu

Jingtao Xu

Jianwen Suo

Tingting Wang

Hao Zhou

Yaling Zhang

Rui Sun

Xiying Zhang

Lili Liu

Shaonan Zhang

Xiaoliang Cong

Weinan Ma

Zhenxi Weng

Chune Lan

The present disclosure provides a method and apparatus for unmanned vehicle dispatching management, a device, a storage medium and a program, which relates to autonomous driving and intelligent transportation technology in artificial intelligence. The specific implementation solution includes: receiving an unmanned vehicle dispatching request; determining, according to the unmanned vehicle dispatching request, a first task type corresponding to a first unmanned vehicle to be dispatched; generating a first order corresponding to the first unmanned vehicle, where the first order is used to indicate a driving task to be performed by the first unmanned vehicle, and a type of the driving task is the first task type; and sending the first order to the first unmanned vehicle. Through the above process, a dispatching management of unmanned vehicles is realized from the task dimension, so that there is no need to distinguish the types of unmanned vehicles.

Method and apparatus for unmanned vehicle dispatching management, device, storage medium and program

Embodiments of the present disclosure provide a method of matching image, an apparatus of matching image, a device, and a computer-readable storage medium. The method includes: acquiring an image to be matched; determining a key point feature similarity between any image in an image library and the image to be matched, and determining a color feature similarity between the any image and the image to be matched; determining a fusion similarity between the any image and the image to be matched according to the key point feature similarity and the color feature similarity; and determining whether an image matching the image to be matched exists in the image library or not according to the fusion similarity between each of at least one image in the image library and the image to be matched.

Method of matching image and apparatus thereof, device, medium and program product

The present disclosure relates to a reverse image search method. The reverse image search method may include receiving a search image; extracting feature points of the search image; finding classes corresponding to the feature points of the search image respectively in an image classification index table, the classes comprising images in an image library; and searching the classes corresponding to the feature points of the search image in the image classification index table to obtain a target image having the largest number of identical feature points of the search image.

Reverse image search method, apparatus and application system

The embodiments of the present disclosure disclose a method and apparatus for extracting an edge of an object in a depth image, a storage medium, and a computer device, to provide a solution which is simple to implement and accurate in edge extraction. The method for extracting an edge of an object in a depth image includes: calculating at least two sets of edge pixels of a first depth image using at least two edge detection algorithms; and acquiring a final set of edge pixels by combining the at least two sets of edge pixels. The solution according to the embodiments of the present disclosure is simple to implement, and may obtain a more accurate set of edge pixels, thereby obtaining an accurate pixel-level segmentation result.

Method and apparatus for extracting edge of object in depth image and computer readable storage medium

The present disclosure provides a shopping recommendation method, a client, and a server. The method includes: acquiring voice information of a user, and performing voice recognition and keyword extraction on the voice information, to obtain shopping keyword information; transmitting the shopping keyword information to a server, so that the server performs interest prediction according to the shopping keyword information and shopping related information of the user, to generate recommendation information; and receiving the recommendation information, and generating shopping recommendation content according to the recommendation information to be displayed by a display.

Shopping recommendation method, client, and server

This disclosure provides an image recommendation method, a client, a server, a computer system and a medium. The method includes acquiring an image, sending the acquired image to a server, such that the server extracts a scale invariant feature of the acquired image and performs retrieval of identical images according to the scale invariant feature of the acquired image, and such that the server extracts a multi-scale feature of the acquired image and performs retrieval of similar images according to the multi-scale feature of the acquired image, and receiving at least one recommended image. The at least one recommended image is based on result of the identical image retrieval and result of the similar image retrieval.

Image recommendation method, client, server, computer system and medium

An object identification method and an object identification device, the object identification method comprises: capturing color images and depth images that are aligned; performing motion detection on the captured color images and depth images to acquire a motion start frame and a motion end frame; comparing the motion end frame with the motion start frame in the color images to acquire a set of motion pixels; performing connected component analysis on the acquired set of motion pixels to obtain at least one connected component; and identifying an object in the at least one connected component.

Object identification method and object identification device

The present disclosure provides an image processing method applied to a vehicle head-up display device, including: determining position information of a target object within a range of activity; acquiring a distortion parameter corresponding to the position information by looking up a table; and performing distortion correction processing on an image to be displayed according to the distortion parameter, so as to obtain a distortion corrected image.

Method and device for image processing, vehicle head-up display system and vehicle

An image search method and an apparatus may include acquiring an image to be searched; extracting a multi-scale feature of the image to be searched; determining a hash value of the image to be searched according to the multi-scale feature; and obtaining original images similar to the image to be searched by comparing the multi-scale feature of the image to be searched with a multi-scale feature of each original image corresponding to a hash bucket to which the hash value belongs.

Image search method and apparatus

The present disclosure provides a navigation method, a shopping cart and a navigation system. The navigation method includes: after a user has selected a shopping cart, associating the user with the shopping cart; acquiring a position of the shopping cart and a parking spot where a vehicle of the user is located; and generating a navigation route in accordance with the position of the shopping cart and the parking spot where the vehicle of the user is located.

Navigation method, shopping cart and navigation system

An automatic object recognition method and an automatic object recognition system, a shopping device and a non-transitory computer readable storage medium are disclosed. The automatic object recognition method includes: acquiring a first image and a second image, both the first image and the second image including a same object, and the second image being a depth image; extracting a feature point of the object based on the first image; obtaining a joint feature based on the feature point from the first image and depth information of the second image; and recognizing the object based on the joint feature.

Automatic object recognition method and system thereof, shopping device and storage medium

A head up display includes: a display source configured to project a correction image and a corrected driving information image onto a transflective component; a polarization controller configured to control a polarization direction of light emitted from the display source; a receiver configured to receive a distorted correction image displayed on the transflective component; and a processor connected with the receiver, and configured to compare the distorted correction image received by the receiver with a correction image pre-stored in the processor to obtain a first image distortion, and to correct a driving information image to be displayed according to the first image distortion to obtain the corrected driving information image.

Head up display, display method thereof and head up display system

The present disclosure provides an image correction method and device. The method includes: correcting a target face image; obtaining first eye position information and second eye position information through calculation according to the face image; obtaining a first image correction parameter and a second image correction parameter via calculation based on the first eye position information and the second eye position information; and correcting a first image according to the first image correction parameter and correcting a second image according to the second image correction parameter.

Image correction method and device

A method of correcting image distortion of an optical device in a display device and a display device are provided. The method includes: generating a plurality of pre-distorted images having different correcting values based on a same reference image; inputting each of the pre-distorted images into the optical device respectively to generate a plurality of display images in one-to-one correspondence to the plurality of pre-distorted images; comparing each of the display images with the reference image respectively, to obtain a display image having a distortion value smaller than a first threshold with respect to the reference image, and determining a correcting value of a pre-distorted image corresponding to this display image as a distortion value of the display device; and correcting the image distortion of the optical device depending on the distortion value of the optical device.

Growing community of inventors

Beijing, China

Xiangyang Liu