International Business Machines Corporation

Qfeeltech (beijing) Co., Ltd.

Ming Chi

Hui Liu

Zhen Chen

Hui Huang

Yiming Zhang

Ang Yi

Shuailing Li

Xiang Shi

Song Bai

Peng Hui Jiang

Si Bin Fan

Qiang Song

A method includes acquiring an image through a visual sensor during a movement of a mobile device. The method includes matching the image with key frames stored in a key frame database. The key frames are created based on two-dimensional coordinates of feature points included in a plurality of images previously acquired through the visual sensor. The method also includes computing a visual relative pose based on two-dimensional coordinates of matching feature points included in both of the image and the one or more key frames that have been matched with the image. The method also includes computing relevant information of the visual relative pose based on the two-dimensional coordinates of the matching feature points. The method further includes updating an absolute pose of the mobile device and a map based on the relevant information of the visual relative pose and relevant information of a dead reckoning based relative pose.

Methods, apparatus, and systems for localization and mapping

A VSLAM method includes receiving an image obtained by a visual sensor. The method also includes retrieving a key frame from a pre-established key frame database, and after the key frame is retrieved, matching the image with the retrieved key frame. The method also includes computing relevant information of a visual relative pose based on the image and the key frame. The visual relative pose is computed based on two-dimensional coordinates of matching feature points between the image and the key frame that have been successfully matched. The method further includes updating an absolute pose and a map of a mobile device based on the relevant information of the visual relative pose and relevant information of a dead reckoning based relative pose, if the relevant information of the visual relative pose is obtained.

An emotion function chain may be generated from an email thread and displayed to a user in one or more windows on a computer display of a computer system. An email content analyzer may extract emotion indicators from the body of an email within the email thread. Using the emotion indicators, an attitude factor for an email may be determined. The attitude factors determined from each email within the email thread may be pictorially depicted in the emotion function chain. In response to a user interaction with a pictorial depiction of an attitude factor within the emotion function chain, a second window may generated to display the body of the email used to calculate the attitude factor interacted with.

Analyzing email threads

According to an embodiment of the present disclosure, it is determined whether a delta index is beneficial based on the difference between a first version and a second version of a document, wherein the first version is associated with a first index comprising a plurality of keywords appeared in the first version. The delta index is generated for the difference between the first and second versions if the delta index is beneficial, wherein the delta index comprises a first section including information about one or more keywords affected by the difference and the information about the positions of the affected keywords.

Generation and use of delta index

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Beijing, China

Ming Chi