Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: In one embodiment, a server receives a request from a first autonomous vehicle for content delivery. In response to the request, a vision analysis is performed on an image obtained from the request to determine three-dimensional (3D) positioning information of the image. A list of content items are identified based on current vehicle information of the first autonomous vehicle in view of a user profile of a user ridding the first autonomous vehicle. A first content item selected from the list of content items is augmented onto the image based on the 3D positioning information of the image, generating an augmented image. The augmented image is transmitted to the first autonomous vehicle, where the augmented image is to be displayed on a display device within the autonomous vehicle in a virtual reality manner.

Abstract: In one embodiment, a cluster manager partitions media data into multiple media data partitions, each of which is to be processed by a computing node of a computing system. A platform module in a computing node receives a number of media files included in a media data partition. The platform module encodes each media file from an original format into a predefined format. The platform module then combines or serializes each encoded media file into a single stream of serialized data, and transmits it to a user module in the computing node. The user module separates from each other the received encoded media files. The user module then decodes each separated, encoded media file from the predefined format into the original format, and performs a specific media processing operation on each decoded file. Examples of the media processing operation include classification, image transformation, and feature extraction.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: In one embodiment, a first image of a physical object external to an autonomous vehicle is received, where the first image is captured by an image sensor attached to the autonomous vehicle. An image recognition is performed on the first image to derive one or more keywords related to the physical object. A list of one or more content items are identified based on the one or more keywords. A first content item selected from the list of content items is augmented onto the first image to generate a second image. The second image is displayed on a display device within the autonomous vehicle.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: The described positional awareness techniques employing sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy. The sensory data are gathered from multiple operational cameras and one or more auxiliary sensors.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: The described positional awareness techniques employing sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy. The sensory data are gathered from an operational camera and one or more auxiliary sensors.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: In one embodiment, an image analysis is performed on an image captured using a camera mounted on an autonomous vehicle, the image representing an exterior environment of an autonomous vehicle. Localization information surrounding the autonomous vehicle is obtained at a point in time. A perception of an audience external to the autonomous vehicle is determined based on the image analysis and the localization information. One or more content items are received from one or more content servers over a network in response to the perception of the audience. A first content item selected from the one or more content items is displayed on a display device mounted on an exterior surface of the autonomous vehicle.

Abstract: A cloud server maintains a neighboring vehicle data structure storing vehicle information of vehicles coupled to the cloud server over a network. The server receives a first request from a first of the vehicles, including a first vehicle identifier (ID) and current vehicle metadata of the first vehicle. In response to the first request, the server traverses the neighboring vehicle data structure to update a first node corresponding to the first vehicle based on the first vehicle ID and the current vehicle information of the first vehicle. The server transmits to the first vehicle over the network a list of one or more vehicle IDs identifying one or more vehicles that are within a predetermined geographic proximity of the first autonomous vehicles to allow the first vehicle to directly communicate with any vehicle in the list via a wireless local area network.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Abstract: In one embodiment, an image analysis is performed on an image captured using a camera mounted on an autonomous vehicle, the image representing an exterior environment of an autonomous vehicle. Localization information surrounding the autonomous vehicle is obtained at a point in time. A perception of an audience external to the autonomous vehicle is determined based on the image analysis and the localization information. One or more content items are received from one or more content servers over a network in response to the perception of the audience. A first content item selected from the one or more content items is displayed on a display device mounted on an exterior surface of the autonomous vehicle.