Microsoft Technology Licensing, LLC

Chunshui Zhao

Chunhui Zhang

Min Wang

Feng Zhao

Rui Gao

Ji Zhao

Fan Li

Yongguang Zhang

Yunxin Liu

Zhengyou Zhang

Jie Jerry Liu

Yasser Baseer Asmi

Qiang Li

Di Wang

Guobin Shen

Jun Hong Zhao

Khawar Zuberi

Jiawei Gu

Richard Harper

George Evangelos Roussos

Mingjie Wang

Tong Yuan

Xiong-Fei Cai

William Thomas

Guobin (Jacky) Shen

Liqun Li

Xiangwei Zhu

Jing Yan

Xiong-Fei (Bruce) Cai

Justin Ayers

Paul Wang

Feng-hsiung Hsu

Shaopeng Song

Huan Ding

The disclosure relates to tracking the location of a target object. In one example, a computer vision system detects a configuration of environment objects. A location model that has been trained for the environment configuration is selected. A signal associated with the target object is received and interpreted using the selected location model to determine the location of the target object.

Location tracking

Techniques for facilitating wireless charging are discussed herein. For example, a power-consuming device may receive a light beam from a charging device. In response, the power-consuming device may determine a power level of a battery associated with the power-consuming device. The power-consuming device may wirelessly signal the power level to the charging device. In some instances, the power-consuming device may determine the power level of the battery without drawing power from the battery. Further, in some instances the power-consuming device may receive another light beam to charge the battery.

Automated charging

Techniques for utilizing two or more mobile devices equipped with projectors to generate a combined seamless user interfaces by stitching projection areas generated by the projectors.

Combined surface user interface

In some implementations, an access device may sense movement in six degrees of freedom for interacting with information in a user interface. In some implementations, a security feature may be included for verifying an authorization of a user to use the access device. Additionally, in some implementations, the access device may establish communication with an available computing device for accessing and interacting with information that may include remotely stored information, cloud data, cloud services, and the like.

Accessing and interacting with information

Example apparatus and methods concern a first off-the-shelf device (e.g., game console, laptop) that may lack a sensor interacting with a second off-the-shelf device(s) (e.g., smart phone, tablet) that has a sensor. The first device may ask remote devices to expose sensors, may select a remote device and sensor to work with, may control communications between the devices and may use the sensor data provided by the second data to run an application on the first device. The application may be acquired from a consumer-oriented application repository, may require sensor data, and may run unmodified on the first device due to the availability of the sensor data from the second device. The combination of devices improves the capability of the first device, saves energy, and reduces computing complexity. A game console or application written for the game console may perform better using sensor data from a remote device.

Sensor data availability from remote devices

Disclosed herein are techniques and systems for performing wireless-based localization using a zonal framework. An area (i.e., surface or space) may be partitioned into multiple zones, and one or more signal propagation models for one or more wireless access points (APs) may be generated for each zone. The result is a set of zonal signal propagation models that allow for improved model fitness on a per-zone basis. A process includes receiving a location query associated with a wireless communication device, selecting a target zone among multiple available zones of an area, and estimating a location of the wireless communication device based at least in part on one of a signal propagation model associated with the target zone or a fingerprint-based localization. The signal propagation model associated with the target zone may be generated based on training samples observed exclusively within the target zone.

Wireless-based localization using a zonal framework

An automated charging device detects a presence of a power-consuming device. The automated charging device may determine whether the power-consuming device is in need of recharging by determining a status of a power level of the power-consuming device. In response to determining that the power-consuming device is due for recharging, the automated charging device may direct a wireless power source to the power-consuming device without user intervention and/or instruction. The automated charging device may detect a location of the power-consuming device and use the detected location to appropriately direct the wireless power source to the power-consuming device.

Technologies pertaining to computing depth images of a scene that includes a mobile object based upon the principle of light falloff are described herein. An infrared image of a scene that includes a mobile object is captured, wherein the infrared image has a plurality of pixels having a respective plurality of intensity values. A depth image for the scene is computed based at least in part upon square roots of respective intensity values in the infrared image.

Generation of depth images based upon light falloff

Techniques for indoor location-finding are described herein. Inside buildings, anomalies in the Earth's magnetic field may be caused by the buildings' structures. These anomalies tend to be location specific and temporally stable. Accordingly, a database or map may be constructed of field strength measurements, and made available to clients, either online (e.g., through cloud services) or offline. As a user carrying a portable device walks within a building, magnetic field measurements may be made. The measurements may be configured in as vectors and compared to the database. A specific location may be indicated by anomaly information seen in both the vector(s) and database. Optionally, techniques may be combined with a particle filter that may be operated step-by-step as the user moves within the building. In another option, fusion with Wi-Fi signals may be performed, such as with a two-pass bidirectional particle filtering.

Indoor location-finding using magnetic field anomalies

A user device is equipped with one or more sensors that collect data relating to a movement of a user having the user device. An estimated area within which a starting location of the user device is located is determined based on one or more signals received from adjacent signal sources. A plurality of candidate locations is identified within the estimated area as the potential starting location of the user device. Map information of surrounding area that covers the estimated area is also obtained. One or more candidate locations are filtered out depending on whether they could have experienced the movement based on the map information. When one or more re-starting conditions have met during the movement, a then starting location of the user device needs to be determined.

Determining user device's starting location

Step detection and step length estimation techniques include detecting salient points in sensor data of one or more sensors. A step frequency is estimated based on a time interval between the detected salient points. A step length of the step may then be computed based on a nonlinear combination of the estimated step frequency and a function of the sensor data, and/or a step model. Alternatively, the step length of the step may be computed based on a combination of a nonlinear function of the estimated step frequency and a (linear or nonlinear) function of the sensor data, and/or a step model.

Step detection and step length estimation

Techniques for utilizing an infrared illuminator, an infrared camera, and a projector to create a virtual 3D model of a real 3D object in real time for users' interaction with the real 3D object.

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Beijing, China

Chunshui Zhao