Abstract: A visual tracker can be configured to obtain profile data associated with a pose of a living entity. In response to detecting a person, a camera can be selected from cameras. Additionally, in response to selecting the camera, the system can receive video data from the camera representative of a stance of the person. Consequently, the stance of the person can be estimated, resulting in an estimated stance.

Abstract: In one example, a processing system of a mobile computing device including at least one processor may capture visual information of a first location, transmit a recognition request to a first server, the recognition request comprising the visual information, obtain a first recognition result from the first server comprising first annotation content associated with a first item in the visual information of the first location, the first recognition result further comprising visual information of the first item, present at least a portion of first annotation content via the mobile computing device, store the first annotation content and the visual information of the first item in a local cache, detect a first additional mobile computing device via a non-cellular wireless communication modality, and share the first annotation content and the visual information of the first item with the first additional mobile computing device via the non-cellular wireless communication modality.

Abstract: Aspects of the subject disclosure may include, for example, a device in which a processing system receives from a multimedia content server a plurality of content streams; each of the content streams includes a portion of an original content stream. The processing system transcodes the plurality of content streams based on a viewport prediction to produce a plurality of viewport streams; the viewport prediction is based at least in part on a visibility map associated with a viewer of the content. The processing system delivers each of the viewport streams to a client device associated with the viewer; each of the viewport streams is buffered at the client device in a separate buffer. Other embodiments are disclosed.

Abstract: In one example, a processing system of a mobile computing device including at least one processor may capture visual information of a first location, transmit a recognition request to a first server, the recognition request comprising the visual information, obtain a first recognition result from the first server comprising first annotation content associated with a first item in the visual information of the first location, the first recognition result further comprising visual information of the first item, present at least a portion of first annotation content via the mobile computing device, store the first annotation content and the visual information of the first item in a local cache, detect a first additional mobile computing device via a non-cellular wireless communication modality, and share the first annotation content and the visual information of the first item with the first additional mobile computing device via the non-cellular wireless communication modality.

Abstract: Aspects of the subject disclosure may include, for example, a device in which a processing system receives from a multimedia content server a plurality of content streams; each of the content streams includes a portion of an original content stream. The processing system transcodes the plurality of content streams based on a viewport prediction to produce a plurality of viewport streams; the viewport prediction is based at least in part on a visibility map associated with a viewer of the content. The processing system delivers each of the viewport streams to a client device associated with the viewer; each of the viewport streams is buffered at the client device in a separate buffer. Other embodiments are disclosed.

Abstract: A visual tracker can be configured to obtain profile data associated with a pose of a living entity. In response to detecting a person, a camera can be selected from cameras. Additionally, in response to selecting the camera, the system can receive video data from the camera representative of a stance of the person. Consequently, the stance of the person can be estimated, resulting in an estimated stance.

Abstract: A processing system having at least one processor may obtain a feature set from a camera frame of a client device, perform a feature reduction of the feature set to produce a reduced feature set, generate a compressed representation from the reduced feature set, compare the compressed representation of the reduced feature set to a plurality of compressed representations of known objects stored in one or more hash tables to identify an object in the camera frame, and provide an identification of the object to the client device.

Abstract: A processing system having at least one processor may obtain a feature set from a camera frame of a client device, perform a feature reduction of the feature set to produce a reduced feature set, generate a compressed representation from the reduced feature set, compare the compressed representation of the reduced feature set to a plurality of compressed representations of known objects stored in one or more hash tables to identify an object in the camera frame, and provide an identification of the object to the client device.

Abstract: An augmented reality device computationally processes an image frame against a first augmented reality profile stored in a local database. The first augmented reality profile includes first annotation content associated with a first object and is obtained from a second user device. In response to an object computationally processed from the first image frame satisfying a predetermined threshold of similarity with the first object in the first augmented reality profile, the first annotation content is rendered, on a display of the first user device, relative to the first object according to rendering instructions for the first annotation content.

Abstract: An augmented reality device computationally processes an image frame against a first augmented reality profile stored in a local database. The first augmented reality profile includes first annotation content associated with a first object and is obtained from a second user device. In response to an object computationally processed from the first image frame satisfying a predetermined threshold of similarity with the first object in the first augmented reality profile, the first annotation content is rendered, on a display of the first user device, relative to the first object according to rendering instructions for the first annotation content.

Abstract: The technology described herein is generally directed towards a free hand, barehanded technique to provide user input to a device, such as to move a cursor on a user interface. Frames of images are captured, and each frame is processed to determine a fingertip position. The processing includes an image segmentation phase that provides a binary representation of the image, a disjoint union arborescence graph construction phase that operates on the binary representation of the image to construct set of arborescence graphs, and a fingertip location estimation phase that selects a graph from among the set of arborescence graphs and uses the root node to estimate the fingertip location. Also described is determining a hand orientation from the set of arborescence graphs.

Abstract: A system for scheduling mobile augmented reality tasks performed on at least one mobile device and a workspace includes: a mobile device, comprising a central processing unit (CPU) and a graphics processing unit (GPU); a Network Profiling Component, configured to gather network related context data; a Device Profiling Component, configured to gather hardware related context data; an Application Profiling Component, configured to gather application related context data; and a Scheduling Component, configured to receive the network related context data, the hardware related context data, and the application related context data, and to schedule tasks between the CPU, the GPU and the workspace.

Abstract: A method for user-desired delay estimation for mobile-cloud applications includes: collecting, by a mobile device, data for a mobile application using at least one of sensors, an application logger and a user feedback module of the mobile device; inferring, by the mobile device, a quality of experience based on the collected data; determining, by the mobile device, a desired delay based on the inferred quality of experience; and offloading, by the mobile device, a task to a cloud together with the desired delay.

Abstract: A method of assisting a full lane change process using at least five cameras provided on a vehicle, a computational device, and an augmented reality device includes: capturing images with the at least five cameras; generating lane change information from the captured images; and displaying the lane change information with the augmented reality device. Generating the lane change information further includes: detecting lanes; detecting the positions and velocities of other vehicles surrounding the vehicle; and generating at least one lane change recommendation.

Abstract: A method for utilizing the computing and/or storage resources of at least one parked vehicle includes recognizing the presence of at least one parked vehicle; establishing a network connection between at least one vehicle communication device of the at least one parked vehicle and at least one server; collecting information from the at least one parked vehicle; dispatching at least one task to the at least one vehicle communication device, wherein the at least one dispatched task comprises at least one of a computational task and a storing task; and performing the at least one dispatched task.

Abstract: A method for utilizing the computing and/or storage resources of at least one parked vehicle includes recognizing the presence of at least one parked vehicle; establishing a network connection between at least one vehicle communication device of the at least one parked vehicle and at least one server; collecting information from the at least one parked vehicle; dispatching at least one task to the at least one vehicle communication device, wherein the at least one dispatched task comprises at least one of a computational task and a storing task; and performing the at least one dispatched task.

Abstract: A system for scheduling mobile augmented reality tasks performed on at least one mobile device and a workspace includes: a mobile device, comprising a central processing unit (CPU) and a graphics processing unit (GPU); a Network Profiling Component, configured to gather network related context data; a Device Profiling Component, configured to gather hardware related context data; an Application Profiling Component, configured to gather application related context data; and a Scheduling Component, configured to receive the network related context data, the hardware related context data, and the application related context data, and to schedule tasks between the CPU, the GPU and the workspace.

Abstract: A method for user-desired delay estimation for mobile-cloud applications includes: collecting, by a mobile application running on a mobile device, data using at least one of sensors, an application logger and a user feedback module of the mobile device; inferring, by the mobile device, a quality of experience based on the collected data; determining, by the mobile device, a desired delay based on the inferred quality of experience; and offloading, by the mobile device, a task to a cloud together with the desired delay.