Microsoft Technology Licensing, LLC

Huawei Technologies Co., Limited

China Academy of Telecommunications Technology

Elekta Beijing Medical Systems Co., Ltd

Xin Tong

Baining Guo

Heung-Yeung Shum

Stephen S Lin

Jiaping Wang

Yang Liu

Xi Wang

Yue Dong

John Michael Snyder

Xiang Cao

Takaaki Shiratori

Nobuyuki Umetani

Yanyun Chen

Yupeng Zhang

Chen Li

Teng Han

Guojun Chen

Zhimin Ren

Jinyu Li

Zhouchen Lin

Minmin Gong

Peiran Ren

Fan Yang

Zicheng Liu

Gang Chen

Li-Yi Wei

Fang Wen

Lifeng Wang

Moshe Benezra

Hsiang-Tao Wu

Xun Cao

Yingnan Ju

Pingchao Yu

Jin-Xiang Chai

Yu Yang

Yuanyuan Li

Qi Zhang

Tong Yang

Tommer Leyvand

Lin Liang

Kristofer Noel Iverson

Peter-Pike Johannes Sloan

David G Molyneaux

Shuang Zhao

Feng Xu

Emmett Walter Lalish

Xiaolu Wang

Wenling Bai

Jay P Kapur

Chenggang Jiang

Simon Stachniak

Eric Chang

Emily Yang

Yulin Jin

Bruno C Silva

Hongbo Jiang

Gheorghe Marius Gheorghescu

Thomas Gersten

Dong Chen

Chongyang Ma

Yangang Wang

Yaohua Hu

Na Qi

Yeming Tang

Ying Hua Song

Ligang Liu

Jian Shi

Li Feng Wang

Andrew Jones

Weicheng Zhao

Jiaolong Yang

Shucheng Fan

Alex Pfaffe

Emmett Lalish

A controller () for a radiotherapy device () is provided; the radiotherapy device () being configured to provide therapeutic radiation to a patient () via a source () of therapeutic radiation, wherein the radiotherapy device () comprises a first rotatable member (), the rotation of which can alter a physical attribute of the therapeutic radiation provided, and a patient support member (), which is linearly moveable in at least one of a longitudinal direction and a lateral direction. The controller () comprises a first rotatable actuator () for controlling a movement of the first rotatable member () and a second actuator () for controlling a movement of the patient support member ().

Controller for radiotherapy device

In accordance with implementations of the present disclosure, there is provided a solution for portrait editing and synthesis. In this solution, a first image about a head of a user is obtained. A three-dimensional head model representing the head of the user is generated based on the first image. In response to receiving a command of changing a head feature of the user, the three-dimensional head model is transformed to reflect the changed head feature. A second image about the head of the user is generated based on the transformed three-dimensional head model, and reflects the changed head feature of the user. In this way, the solution can realize editing of features like a head pose and/or a facial expression based on a single portrait image without manual intervention and automatically synthesize a corresponding image.

Portrait editing and synthesis

Implementations of the subject matter described herein relate to mixed reality object rendering based on ambient light conditions. According to the embodiments of the subject matter described herein, while rendering an object a wearable computing device acquires light conditions of the real world, thereby increasing the reality of the rendered object. In particular, the wearable computing deice is configured to acquire an image of an environment where the wearable computing deice is located. The image is adjusted based on a cement parameter used when the image is captured. Subsequently, ambient light information is determined based on the adjusted image. In this way, the wearable computing deice can obtain more real and accurate emblem light information, so as to render to the user an object with enhanced reality. Accordingly, the user can have a better interaction experience.

Ambient light based mixed reality object rendering

Implementations of the subject matter described herein relate to mixed reality object rendering based on ambient light conditions. According to the embodiments of the subject matter described herein, while rendering an object, a wearable computing device acquires light conditions of the real world, thereby increasing the reality of the rendered object. In particular, the wearable computing device is configured to acquire an image of an environment where the wearable computing device is located. The image is adjusted based on a camera parameter used when the image is captured. Subsequently, ambient light information is determined based on the adjusted image. In this way, the wearable computing device can obtain more real and accurate ambient light information, so as to render to the user an object with enhanced reality. Accordingly, the user can have a better interaction experience.

An intuitive interface may allow users of a computing device (e.g., children, etc.) to create imaginary three dimensional (3D) objects of any shape using body gestures performed by the users as a primary or only input. A user may make motions while in front of an imaging device that senses movement of the user. The interface may allow first-person and/or third person interaction during creation of objects, which may map a body of a user to a body of an object presented by a display. In an example process, the user may start by scanning an arbitrary body gesture into an initial shape of an object. Next, the user may perform various gestures using his body, which may result in various edits to the object. After the object is completed, the object may be animated, possibly based on movements of the user.

Object creation using body gestures

Implementations of the subject matter described herein relate to mixed reality rendering of objects. According to the embodiments of the subject matter described herein, while rendering an object, a wearable computing device takes lighting conditions in the real world into account, thereby increasing the reality of the rendered object. In particular, the wearable computing device acquires environment lighting information of an object to be rendered and renders the object to a user based on the environment lighting information. In this way, the object rendered by the wearable computing device can be more real and accurate. The user will thus have a better interaction experience.

Mixed reality object rendering based on environment lighting

In accordance with implementations of the subject matter described herein, there is provided a solution of lighting estimation. In the solution, an input image about a real object and a depth map corresponding to the input image are obtained. A geometric structure of the scene in the input image is determined based on the depth map. Shading and shadow information on the real object caused by a light source in the scene is determined based on the determined geometric structure of the scene. Then, a lighting condition in the scene caused by the light source is determined based on the input image and the shading and shadow information. The virtual object rendered using the lighting condition obtained according to the solution can exhibit a realistic effect consistent with the real object.

Lighting estimation using an input image and depth map

The present disclosure provides method, apparatus and system for 3-dimension (3D) face tracking. The method for 3D face tracking may comprise: obtaining a 2-dimension (2D) face image; performing a local feature regression on the 2D face image to determine 3D face representation parameters corresponding to the 2D face image; and generating a 3D facial mesh and corresponding 2D facial landmarks based on the determined 3D face representation parameters. The present disclosure may improve tracking accuracy and reduce memory cost, and accordingly may be effectively applied in broader application scenarios.

Method, apparatus and system for 3D face tracking

Techniques and constructs can determine an albedo map and a shading map from a digital image. The albedo and shading maps can be determined based at least in part on a color-difference threshold. A color shading map can be determined based at least in part on the albedo map, and lighting coefficients determined based on the color shading map. The digital image can be adjusted based at least in part on the lighting coefficients. In some examples, respective shading maps can be produced for individual color channels of the digital image. The color shading map can be produced based at least in part on the shading maps. In some examples, a plurality of regions of the digital image can be determined, as can proximity relationships between individual regions. The albedo shading maps can be determined based at least in part on the proximity relationships.

Machine vision processing system

In this disclosure, a solution for denoising a curve mesh is proposed. For a curve mesh including a polygonal facet, a noisy normal and a ground-truth normal of a first facet in the mesh is obtained. Then, based on the noisy normal, a first geometric feature of the first facet is determined from a plurality of neighboring facets of the first facet in the mesh. Next, based on the first geometric feature and the ground-truth normal, a mapping from the first geometric feature to the ground-truth normal of the first facet is determined for denoising the mesh.

Mesh denoising

The claimed subject matter includes techniques for printing three-dimensional (3D) objects. An example method includes obtaining a 3D model and processing the 3D model to generate layers of tool path information. The processing includes automatically optimizing the orientation of the 3D model to reduce an amount of support material used in the printing. The method also includes printing the 3D object using layers.

Fabricating three dimensional objects

The use of a hybrid camera tool may capture high resolution multispectral images without sacrificing resolution in exchange for spectral accuracy. The capture of a high resolution multispectral image may include forming a high spatial resolution image based on a portion of incoming light and generating a high spectral resolution image that includes multispectral samples based on another portion of the incoming light. The high resolution multispectral image is then synthesized by consolidating the high spatial resolution image with the high spectral resolution image.

High resolution multispectral image capture

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Beijing, China

Xin Tong