Microsoft Technology Licensing, LLC

Beijing Xiaomi Mobile Software Co., Ltd.

Rui Cai

Lei Zhang

Wei-Ying Ma

Zhiwei Li

Wei Wang

Haifeng Li

Jiang-Ming Yang

Xiao Kong

Qiang Hao

Yanfeng Sun

Jiangming Yang

Wei Lin Lai

Heung-Yeung Shum

Hao Liu

Arthur Charles Tomlin

Chi Zhang

Michael Scavezze

Changhu Wang

Rong Xiao

Kun Guo

Xiaodong Fan

Kuiyuan Yang

Chao Wang

Yong Rui

Jiawei Gu

Hao Li

Yan Ke

Xin-Jing Wang

Xiaosong Yang

Wenbin Tang

Shouqiu Yu

Zhijun Xie

A method and an apparatus for vehicle positioning. The method includes: acquiring a distance transformation image of a road marking object in a road image based on the road image of an environment where a vehicle is located at a current time point; acquiring a vector subgraph of the road marking object from a global vector map; and determining a target positioning posture of the vehicle based on the distance transformation image and the vector subgraph.

Method and apparatus for vehicle positioning

A vehicle localization method and device, an electronic device and a storage medium. The vehicle localization method includes: acquiring an image of a scene where a vehicle is located, the image comprising a semantic element; determining an element category corresponding to the semantic element; matching the semantic element with a map element to acquire a matching result by a matching method corresponding to the element category; and determining localization information of the vehicle according to the matching result.

Vehicle localization method and device, electronic device and storage medium

Sensor fusion is utilized in an electronic device such as a head mounted display (HMD) device that has a sensor package equipped with different sensors so that information that is supplemental to captured 2D images of objects or scenes in a real world environment may be utilized to determine an optimized transform of image stereo-pairs and to discard erroneous data that would otherwise prevent successful scans used for construction of a 3D model in, for example, virtual world applications. Such supplemental information can include one or more of world location, world rotation, image data from an extended field of view (FOV), or depth map data.

Optimized object scanning using sensor fusion

Web crawling polices are generated based on user web browsing statistics. User browsing statistics are aggregated at the granularity of resource identifier patterns (such as URL patterns) that denote groups of resources within a particular domain or website that share syntax at a certain level of granularity. The web crawl policies rank the resource identifier patterns according to their associated aggregated user browsing statistics. A crawl ordering defined by the web crawl polices is used to download and discover new resources within a domain or website.

Resource download policies based on user browsing statistics

Described herein is a technology that facilitates efficient large-scale similarity-based retrieval. In several embodiments documents, images, and/or other multimedia files are compactly represented and efficiently indexed to enable robust search using a long-query in a large-scale corpus. As described herein, these techniques include performing decomposition of a file, e.g., an image, a document containing an image, or a document-like representation of an image. The techniques use dimension reduction to obtain three parts, low-dimensional representations (major semantics), file specific terms (minor semantics), and background words, representing the major semantics in a feature vector and the minor semantics as keywords. Using the techniques described, file vectors are matched in a topic model and the results ranked based on the keywords.

Long-query retrieval

Anchor images and information associated therewith are accumulated during a Web crawling operation. One or more rules are applied to the accumulated candidate anchor images to filter out candidate anchor images that are not appropriate for use as the anchor image for a particular target video. The remaining candidate anchor image is then selected as the anchor image for the particular video.

Anchor image identification for vertical video search

A method of acquiring a set of images useable to 3D model a physical object includes imaging the physical object with a camera, and displaying with the camera a current view of the physical object as imaged by the camera from a current perspective. The method further includes displaying with the camera a visual cue overlaying the current view and indicating perspectives from which the physical object is to be imaged to acquire the set of images.

User interface for three-dimensional modeling

Tools and techniques for identifying visual contextual synonyms are described herein. The described operations use visual words having similar contextual distributions as contextual synonyms to identify and describe visual objects that share semantic meaning. The contextual distribution of a visual word is described using the statistics of co-occurrence and spatial information averaged over image patches that share the visual word. In various implementations, the techniques are employed to construct a visual contextual synonym dictionary for a large visual vocabulary. In various implementations, the visual contextual synonym dictionary narrows the semantic gap for large-scale visual search.

Identifying visual contextual synonyms

The techniques discussed herein discover three-dimensional (3-D) visual phrases for an object based on a 3-D model of the object. The techniques then describe the 3-D visual phrases. Once described, the techniques use the 3-D visual phrases to detect the object in an image (e.g., object recognition).

Three-dimensional visual phrases for object recognition

Described herein is a technology that facilitates efficient automated mining of topic-related aspects of user-generated content based on automated analysis of the user-generated content. Locations are automatically learned based on dividing documents into document segments, and decomposing the segments into local topics and global topics. Techniques are described that facilitate automatically extracting snippets. These techniques include, for example, computer annotating travelogues with learned tags and images, performing topic learning to obtain an interest model, performing location matching based on the interest model, calculating geographic and semantic relevance scores, ranking snippets based on the geographic and semantic relevance scores, and searching snippets with a 'location+context term' query.

Snippet extraction and ranking

This document describes techniques that label text nodes of a seed site for each of a plurality of verticals. Once a seed site is labeled for a given vertical, the techniques extract features from the labeled text nodes of the seed site. The techniques learn vertical knowledge for the seed site based on the human labels and the extracted features, and adapt the learned vertical knowledge to a new web site to automatically and accurately identify attributes and extract attribute values targeted within a given vertical for structured web data extraction.

Flexible and scalable structured web data extraction

A method and system for identifying informative links of a web site for use in crawling the web site is provided. A forum crawler analyzes sample web pages of a web forum to identify informative links and then crawls the web forum by following links determined to be informative and not following other links. The forum crawler system determines whether links are informative based on whether they are part of the overall structure of the web site or are used to select sequential information that has been split onto multiple web pages.

Web forum crawling using skeletal links

An exemplary method includes defining a vocabulary for emotions; extracting descriptions for songs; generating distributions for the songs in an emotion space based at least in part on the vocabulary and the extracted descriptions; extracting salient words from a document; generating a distribution for the document in an emotion space based at least in part on the vocabulary and the extracted salient words; and matching the distribution for the document to one or more of the distributions for the songs. Various other exemplary methods, devices, systems, etc., are also disclosed.

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Beijing, China

Rui Cai