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:
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:
Disclosed are systems and methods for providing a rules engine as a platform within a portable electronic device. In one embodiment, a rules engine platform is provided within a portable electronic device by receiving a plurality of rules for one or more modules of the portable electronic device. Additionally, the rules engine platform can receive one or more samples from one or more of the modules within the portable electronic device. The rules engine platform identifies and evaluates one or more relevant rules based on the received sample. The rules engine platform can then determine an action to provide to other modules of the portable electronic device. The rules engine platform may be configured to optimize the performance and power consumption of the portable electronic device.
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 mobile platform efficiently processes sensor data, including 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 sensor data, such as image data, and determines whether there is a trigger event to transmit the sensor data to the server. The trigger event may be a change in the sensor data relative to previously acquired sensor data, e.g., a scene change in an image. When a change is present, the sensor data may be transmitted to the server for processing. The server processes the sensor data and returns information related to the sensor 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 multi-user augmented reality (AR) system operates without a previously acquired common reference by generating a reference image on the fly. The reference image is produced by capturing at least two images of a planar object and using the images to determine a pose (position and orientation) of a first mobile platform with respect to the planar object. Based on the orientation of the mobile platform, an image of the planar object, which may be one of the initial images or a subsequently captured image, is warped to produce the reference image of a front view of the planar object. The reference image may be produced by the mobile platform or by, e.g., a server. Other mobile platforms may determine their pose with respect to the planar object using the reference image to perform a multi-user augmented reality application.
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:
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:
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.