Intel Corporation

Gm Global Technolgoy Operations, Inc.

Kobi Nistel

Gila Kamhi

Barak Hurwitz

Michael Baltaxe

Vladimir Kouperman

Ron Ferens

Amit Moran

Ruben Mergui

Scott David Thomas

Nadav Zamir

Vladimir Cooperman

Dorel M Sala

Eli Tzirkel-Hancock

Asaf Degani

Yael Shmueli Friedland

Dror Reif

Lisa A Fallon

Michal Genussov Ziss

Itai Druker

David Chettrit

Vision-based airbag enablement may include capturing two-dimensional images of a passenger, segmenting the image, classifying the image, and determining seated height of the passenger from the image. Enabling or disabling deployment of the airbag may be controlled based at least in part upon the determined seated height.

Vision-based airbag enablement

A system includes a seat belt routing module and a user interface device (UID) control module. The seat belt routing module is configured to: determine a routing of a seat belt relative to an occupant in a vehicle seat based on input from a webbing payout sensor; and determine the seat belt routing based on an input from an in-cabin sensor. The in-cabin sensor includes at least one of a camera, an infrared sensor, an ultrasonic sensor, a radar sensor, and a lidar sensor. The UID control module is configured to control a user interface device to indicate that the seat belt is being worn improperly when: the seat belt routing determined using at least one of the webbing payout sensor and the in-cabin sensor is improper; and the seat belt routing determined using the webbing payout sensor corresponds to the seat belt routing determined using the in-cabin sensor.

System and method for monitoring seat belt routing using both a webbing payout sensor and an in-cabin sensor

A system for interacting with a user in a vehicle includes a processing device including an input module configured to receive measurement data from one or more sensors, the measurement data related to features of the user. The system also includes a prompt design module configured to, in response to receiving an instruction to output a requested prompt to the user, determine a user state based on the measurement data, determine an activity state based on the measurement data and the user state, customize the requested prompt based on the user state and the activity state to generate a customized prompt, and output the customized prompt to the user.

User activity-based customization of vehicle prompts

A system for detecting seatbelt routing includes: a state module configured to, based on a series of images over a period of time from a camera of a vehicle facing a seat, determine and output a routing state of a seatbelt of the seat; and a remediation module configured to, based on the routing state of the seatbelt of the seat, selectively perform at least one remedial action.

Time based seatbelt routing detection via in-cabin sensors

An augmented reality (AR) device includes a 3D video camera to capture video images and corresponding depth information, a display device to display the video data, and an AR module to add a virtual 3D model to the displayed video data. A depth mapping module generates a 3D map based on the depth information, a dynamic scene recognition and tracking module processes the video images and the 3D map to detect and track a target object within a field of view of the 3D video camera, and an augmented video rendering module renders an augmented video of the virtual 3D model dynamically interacting with the target object. The augmented video is displayed on the display device in real time. The AR device may further include a context module to select the virtual 3D model based on context data comprising a current location of the augmented reality device.

Systems and methods for contextually augmented video creation and sharing

A seat belt status determining system and method for a vehicle that evaluate a seat belt and determine if it is buckled and if it is properly routed on a passenger. In order to evaluate the seat belt status, the system and method use seat belt sensors and cameras inside the vehicle cabin to generate data that is then analyzed in conjunction with machine learning techniques (e.g., supervised machine learning techniques implemented through the use of neural networks) to classify the seat belt status into one or more categories, such as: passenger not present, passenger present/seat belt not being worn, passenger present/seat belt being worn improperly, passenger present/seat belt being worn properly, and blocked view.

Seat belt status determining system and method

Apparatuses, systems, media and/or methods may involve creating content. A property component may be added to a media object to impart one or more of a perceptual property or a contextual property to the media object. The property component may be added responsive to an operation by a user that is independent of a direct access by the user to computer source code. An event corresponding to the property component may be mapped with an action for the media object. The event may be mapped with the action responsive to an operation by a user that is independent of a direct access by the user to computer source code. A graphical user interface may be rendered to create the content. In addition, the media object may be modified based on the action in response to the event when content created including the media object is utilized.

Media content including a perceptual property and/or a contextual property

A method of augmented projection for vehicle passengers includes sensing that the passenger is within, or about to enter, a drop zone, and sensing one or more static obstacles within the drop zone. The method further includes highlighting at least one of the static obstacles with a projector mounted on the vehicle.

Real-time analysis and augmented pathway projection for vehicle passengers

This disclosure pertains to machine object determination based on human interaction. In general, a device such as a robot may be capable of interacting with a person (e.g., user) to select an object. The user may identify the target object for the device, which may determine whether the target object is known. If the device determines that target object is known, the device may confirm the target object to the user. If the device determines that the target object is not known, the device may then determine a group of characteristics for use in determining the object from potential target objects, and may select a characteristic that most substantially reduces a number of potential target objects. After the characteristic is determined, the device may formulate an inquiry to the user utilizing the characteristic. Characteristics may be selected until the device determines the target object and confirms it to the user.

Machine object determination based on human interaction

Computer-readable storage media, computing device and methods associated with dynamic modification of a rendering of a physical scene. In embodiments, one or more computer-readable storage media may have instructions stored thereon which, when executed by a computing device, may provide the computing device with a dynamic augmentation module. The dynamic augmentation module may, in some embodiments, cause the computing device to receive a manipulation of a physical scene. In response to receipt of the manipulation, the dynamic augmentation module may cause the computing device to dynamically modify a rendering of the physical scene. In some embodiments, this may be accomplished through real-time application of one or more virtual articles to the rendering of the physical scene or alteration of one or more virtual articles added to the rendering of the physical scene. Other embodiments may be described and/or claimed.

Dynamic augmentation of a physical scene

A narrative presentation system may include at least one optical sensor capable of detecting objects added to the field-of-view of the at least one optical sensor. Using data contained in signals received from the at least one optical sensor, an adaptive narrative presentation circuit identifies an object added to the field-of-view and identifies an aspect of a narrative presentation logically associated with the identified object. The adaptive narrative presentation circuit modifies the aspect of the narrative presentation identified as logically associated with the identified object.

Interactive adaptive narrative presentation

Disclosed in some examples are methods systems and machine readable mediums in which actions or states of a first user (e.g., natural interactions) having a first corresponding computing device are observed by a sensor on a second computing device corresponding to a second user. A notification describing the observed actions or states of a first user may be shared across a network with the first corresponding computing device. In this way, the first computing device may be provided with information concerning the state of the user without having to directly sense the user.

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Haifa, Israel

Kobi Nistel