Intel Corporation

Ayoob Nabwani

Tomer Rider

Wenlong Yang

Ofir Natan

Artyom Khvediouk

Saar Amzaleg

Vladimir Colton

A vehicle () may include one or more image sensors () configured to provide sensor image data () representing a sensor image of a vicinity of the vehicle (), and one or more processors () configured to determine one or more obstacles () from the sensor image data (), to determine a distance from ground for each of the one or more obstacles () based its corresponding image object (), and to trigger a safety operation when the distance from ground is equal to or less than a safety height associated with the vehicle (). A method for avoiding a collision of a vehicle with one or more obstacles.

Vehicle and method for avoiding a collision of a vehicle with one or more obstacles

Systems, apparatuses and methods may leverage technology that recognizes a set of one or more hands in one more frames of a video signal during a first gesture control interaction between the set of one or more hands and an electronic device. Moreover, one or more additional body parts may be detected in the frame(s), wherein the additional body part(s) are excluded from the gesture control interaction. In one example, detecting the additional body part(s) includes determining that the additional body part(s) correspond to a different individual than a target individual associated with the set of hand(s).

Gesture experiences in multi-user environments

A system is described. The system includes one or more sensing devices to acquire depth image data, scan logic to scan the depth image data for moving objects, vehicle recognition logic to recognize an automobile in the scanned image data, capture a registered plate number of the automobile and connect with the automobile based on the captured registered plate number and object recognition logic to recognize a presence of one or more moving objects in the depth image data that are about to come across a path of the automobile.

Smart mirror mechanism

Emotion detection systems disclosed herein actively protect the privacy and security of monitored subjects. This provision of protection differentiates these systems from conventional emotion detectors. In some examples, a self-contained emotion detection device protects the identity of a subject while providing anonymous data descriptive of the subject's emotional state to other devices within the emotion detection system. In these examples, the emotion detection device protects the identity of the subject by isolating raw image data acquired by the device exclusively within storage locations encapsulated within the device. To provide the anonymous data, the emotion detection device first processes the raw image data to identify landmark points within an image of the subject's face. Next, the emotion detection device normalizes the landmark points to a generic face and transmits an anonymous data set descriptive of the normalized landmark points to the other devices for subsequent processing.

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Haifa, Israel

Ayoob Nabwani