Abstract: A method for calibrating a device having a first sensor and a second sensor. The method includes capturing sensor data using the first sensor and the second sensor. The device maintains a calibration profile including a translation parameter and a rotation parameter to model a spatial relationship between the first sensor and the second sensor. The method also includes determining a calibration level associated with the calibration profile at a first time. The method further includes determining, based on the calibration level, to perform a calibration process. The method further includes performing the calibration process at the first time by generating one or both of a calibrated translation parameter and a calibrated rotation parameter and replacing one or both of the translation parameter and the rotation parameter with one or both of the calibrated translation parameter and the calibrated rotation parameter.

Abstract: To determine the head pose of a user, a head-mounted display system having an imaging device can obtain a current image of a real-world environment, with points corresponding to salient points which will be used to determine the head pose. The salient points are patch-based and include: a first salient point being projected onto the current image from a previous image, and with a second salient point included in the current image being extracted from the current image. Each salient point is subsequently matched with real-world points based on descriptor-based map information indicating locations of salient points in the real-world environment. The orientation of the imaging devices is determined based on the matching and based on the relative positions of the salient points in the view captured in the current image. The orientation may be used to extrapolate the head pose of the wearer of the head-mounted display system.

Abstract: An apparatus and method for a framework exposing an API (application programming interface) to web-based server applications on the internet or in the cloud is presented. The API allows server applications to retrieve sensor data from a mobile device via a low-power sensor core processor on a mobile device. This API eliminates effort and cost associated with developing and promoting a new mobile device client application. The API framework includes APIs that web-based application may use to fetch sensor data from one or more particular sensors on the mobile device.

Abstract: A method of auto-calibrating light sensor data of a mobile device includes, obtaining, by the mobile device, one or more reference parameters representative of light sensor data collected by a reference device. The method also includes collecting, by the mobile device, light sensor data from a light sensor included in the mobile device, itself. One or more sample parameters of the light sensor data obtained from the light sensor included in the mobile device are then calculated. A calibration model is then determined for auto-calibrating the light sensor data of the light sensor included in the mobile device based on the one or more reference parameters and the one or more sample parameters.

Abstract: A mobile device, such as a smartphone or a tablet computer, can execute functionality for configuring a network device in a communication network and for subsequently controlling the operation of the network device with little manual input. The mobile device can detect sensor information from a network device. The mobile device can determine device configuration information based, at least in part, on decoding the sensor information. The mobile device can provide the device configuration information to an access point of a network. The mobile device can receive communication link information from the access point. The mobile device can provide the communication link information to the network device. The mobile device can receive a message indicating a communication link between the network device and the access point is established.

Abstract: Methods, systems, and techniques to enhance computer vision application processing are disclosed. In particular, the methods, systems, and techniques may reduce power consumption for computer vision applications and improve processing efficiency for computer vision applications.

Abstract: Methods and apparatus relating to enabling augmented reality applications using eye gaze tracking are disclosed. An exemplary method according to the disclosure includes displaying an image to a user of a scene viewable by the user, receiving information indicative of an eye gaze of the user, determining an area of interest within the image based on the eye gaze information, determining an image segment based on the area of interest, initiating an object recognition process on the image segment, and displaying results of the object recognition process.

Abstract: Methods and apparatus relating to enabling augmented reality applications using eye gaze tracking are disclosed. An exemplary method according to the disclosure includes displaying an image to a user of a scene viewable by the user, receiving information indicative of an eye gaze of the user, determining an area of interest within the image based on the eye gaze information, determining an image segment based on the area of interest, initiating an object recognition process on the image segment, and displaying results of the object recognition process.

Abstract: Systems and methods for performing localization and mapping with a mobile device are disclosed. In one embodiment, a method for performing localization and mapping with a mobile device includes identifying geometric constraints associated with a current area at which the mobile device is located, obtaining at least one image of the current area captured by at least a first camera of the mobile device, obtaining data associated with the current area via at least one of a second camera of the mobile device or a sensor of the mobile device, and performing localization and mapping for the current area by applying the geometric constraints and the data associated with the current area to the at least one image.

Abstract: A method of performing context inference is described. The method includes collecting ambient light at a spectrometer sensor integrated in a portable device, characterizing the collected light to obtain optical information, comparing the optical information to optical data predetermined to match one or more contexts, inferring at least one characteristic of a specific context based on the comparison, and determining a probability that the portable device is in the specific context.

Abstract: A detector in a mobile device receives input from a modem, determines whether the mobile device is indoor or outdoor based on the modem-supplied input, and stores in memory a binary value to indicate an indoor-outdoor state. In some embodiments, the detector extracts a feature from the modem-supplied input, and uses the extracted feature with a statistical classifier, to output an indoor-outdoor state and an associated probability of correctness of the indoor-outdoor state, in other embodiments, the detector determines whether the mobile device is indoor or outdoor based at least on the feature extracted to characterize temporal distribution of the wireless signal, by using a prior value of the state being indoor or outdoor.

Abstract: A confidentiality preserving system and method for performing a rank-ordered search and retrieval of contents of a data collection. The system includes at least one computer system including a search and retrieval algorithm using term frequency and/or similar features for rank-ordering selective contents of the data collection, and enabling secure retrieval of the selective contents based on the rank-order. The search and retrieval algorithm includes a baseline algorithm, a partially server oriented algorithm, and/or a fully server oriented algorithm. The partially and/or fully server oriented algorithms use homomorphic and/or order preserving encryption for enabling search capability from a user other than an owner of the contents of the data collection. The confidentiality preserving method includes using term frequency for rank-ordering selective contents of the data collection, and retrieving the selective contents based on the rank-order.

Abstract: Systems and methods share context information on a neighbor aware network. In one aspect, a context providing device receives a plurality of responses to a discovery query from a context consuming device, and tailors services it offers to the context consuming device based on the responses. In another aspect, a context providing device indicates in its response to a discovery query which services or local context information it can provide to the context consuming device, and also a cost associated with providing the service or the local context information. In some aspects, the cost is in units of monetary currency. In other aspects, the cost is in units of user interface display made available to an entity associated with the context providing device in exchange for the services or local context information offered to the context consuming device.

Abstract: Embodiments of the present invention are directed toward providing intelligent sampling strategies that make efficient use of an always-on camera. To do so, embodiments can utilize sensor information to determine contextual information regarding the mobile device and/or a user of the mobile device. A sampling rate of the always-on camera can then be modulated based on the contextual information.

Abstract: A mobile platform efficiently processes image data, using distributed processing in which latency sensitive operations are performed on the mobile platform, while latency insensitive, but computationally intensive operations are performed on a remote server. The mobile platform acquires image data, and determines whether there is a trigger event to transmit the image data to the server. The trigger event may be a change in the image data relative to previously acquired image data, e.g., a scene change in an image. When a change is present, the image data may be transmitted to the server for processing. The server processes the image data and returns information related to the image data, such as identification of an object in an image or a reference image or model. The mobile platform may then perform reference based tracking using the identified object or reference image or model.

Abstract: A context aware system, for use in a mobile device, includes a context change detector (CCD) coupled to a context classifier (CCL). The CCD is configured to receive sensor data and to detect a change in a current context state of the mobile device based on the received sensor data. The CCL is configured to transition from a low power consumption mode to a normal power consumption mode in response to the CCD detecting the change in the current context state. The CCL is further configured to determine a next context state of the mobile device while in the normal power consumption mode.

Abstract: Methods, systems, computer-readable media, and apparatuses for determining indoor/outdoor state of a mobile device are presented. In some embodiments, a sensor reading is obtained from a sensor accessible by the mobile device. Contemporaneous information related to a local condition associated with an area where the mobile device is located is obtained. At least the sensor reading and the information related to a local condition are provided as input to an indoor/outdoor detection model selected from a plurality of trained models. Based on the model, the mobile device is classified as indoors or outdoors.

Abstract: A method of auto-calibrating light sensor data of a mobile device includes, obtaining, by the mobile device, one or more reference parameters representative of light sensor data collected by a reference device. The method also includes collecting, by the mobile device, light sensor data from a light sensor included in the mobile device, itself. One or more sample parameters of the light sensor data obtained from the light sensor included in the mobile device are then calculated. A calibration model is then determined for auto-calibrating the light sensor data of the light sensor included in the mobile device based on the one or more reference parameters and the one or more sample parameters.

Abstract: A three-dimensional pose of the head of a subject is determined based on depth data captured in multiple images. The multiple images of the head are captured, e.g., by an RGBD camera. A rotation matrix and translation vector of the pose of the head relative to a reference pose is determined using the depth data. For example, arbitrary feature points on the head may be extracted in each of the multiple images and provided along with corresponding depth data to an Extended Kalman filter with states including a rotation matrix and a translation vector associated with the reference pose for the head and a current orientation and a current position. The three-dimensional pose of the head with respect to the reference pose is then determined based on the rotation matrix and the translation vector.

Abstract: A vision based tracking system in a mobile platform tracks objects using groups of detected lines. The tracking system detects lines in a captured image of the object to be tracked. Groups of lines are formed from the detected lines. The groups of lines may be formed by computing intersection points of the detected lines and using intersection points to identified connected lines, where the groups of lines are formed using connected lines. A graph of the detected lines may be constructed and intersection points identified. Interesting subgraphs are generated using the connections and the group of lines is formed with the interesting subgraphs. Once the groups of lines are formed, the groups of lines are used to track the object, e.g., by comparing the groups of lines in a current image of the object to groups of lines in a previous image of the object.