Intel Corporation

Jonathan Thompson

Paul Winer

Anders Grunnet-Jepsen

John N Sweetser

Akihiro Takagi

Garth Shoemaker

Leonid Keselman

Steven S Bateman

Chandrika Jayant

Physiological cues, such as elevated heart or respiratory rates can be masked from video of a person before the video is sent to another party. The masking of human-perceptible and non-human-perceptible physiological cues removes information from the video that another party could use to determine the person's emotional state. For example, variations in a person's skin color that are typically imperceptible to the human eye and from which a person's heart rate can be detected, can be removed or altered so that another party viewing the video cannot determine the person's actual heart rate in an attempt to determine the person's emotional state, even if they are performing computer analysis on the video. The presence of some physiological cues can be determined by detecting that a physiological measure is above a specified physiological measure threshold. Modified video can have the characteristic that physiological cues are substantially absent in the modified video or that physiological measures extracted from the modified video have a value below an associated physiological measure threshold.

Physiological cue processing

Embodiments of a system and method for detecting a leading stroke risk indicator using low-cost, non-contact visual computing methods are generally described herein. In some embodiments, a video camera is arranged to capture a video of a face of a subject to be evaluated for having a stroke risk indicator. A memory is provided for storing data. A processor is coupled to the memory and is arranged to analyze processed image data associated with the video of the face of the subject captured by the video camera. The processor is further arranged to determine whether the processed image data exhibits a leading indicator for carotid artery stenosis.

Detection of a leading stroke risk indicator

Apparatus, computer-readable storage medium, and method associated with human computer interaction. In embodiments, a computing device may include a plurality of sensors, including a plurality of light sources and a camera, to create a three dimensional (3-D) interaction region within which to track individual finger positions of a user of the computing device. The light sources and the camera may be complementarily disposed for the camera to capture the finger or hand positions. The computing device may further include a 3-D interaction module configured to analyze the individual finger positions within the 3-D interaction region, the individual finger movements captured by the camera, to detect a gesture based on a result of the analysis, and to execute a user control action corresponding to the gesture detected. Other embodiments may be described and/or claimed.

Gesture based human computer interaction

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Santa Clara, CA, United States of America

Jonathan Thompson