Abstract: A facial skin mask may be generated based on isolating a head part in a captured image, removing a first pixel that is indicative of non-skin from the head part in the captured image, and removing a second pixel that is indicative of having a high velocity from the head part in the captured image. Heart rate may be detected based on the change of color of the pixels of the generated facial skin mask.

Abstract: A facial skin mask may be generated based on isolating a head part in a captured image, removing a first pixel that is indicative of non-skin from the head part in the captured image, and removing a second pixel that is indicative of having a high velocity from the head part in the captured image. Heart rate may be detected based on the change of color of the pixels of the generated facial skin mask.

Abstract: A facial skin mask may be generated based on isolating a head part in a captured image, removing a first pixel that is indicative of non-skin from the head part in the captured image, and removing a second pixel that is indicative of having a high velocity from the head part in the captured image. Heart rate may be detected based on the change of color of the pixels of the generated facial skin mask.

Abstract: Heartrate tracking is performed entirely optically without the subject being required to wear any monitoring equipment by processing a combination of signals representing frames of video of the sinusoidal motion of a subject's facial skin color changes captured by both IR and visible light (e.g., RGB—red/green/blue) cameras. The IR and RGB graphs that result from the processing are perfectly phase-shifted so that when the IR signal is going down in amplitude, the RGB signal is going up. Such phase-shifting enables the optical heartrate tracking to utilize diverse input feeds so that a tracked signal is accepted as the user's true heartrate when both IR and RGB signals are well correlated.

Abstract: Embodiments described herein use depth images to extract user behavior, wherein each depth image specifies that a plurality of pixels correspond to a user. In certain embodiments, one or more average extremity positions of a user, which can also be referred to as average positions of extremity blobs, are extracted from a depth image. An application is then updated based on the average positions of extremity blobs.

Abstract: An active illumination range camera that acquires a range and a picture image of a scene and provides a reflectance for a feature in the scene responsive to a distance for the feature provided by the range image, a registered irradiance for the feature provided by the picture image and registered irradiance for a region of a calibration surface corresponding to the feature provided by an image of the calibration surface acquired by the range camera.

Abstract: Embodiments described herein can be used to detect holes in a subset of pixels of a depth image that has been specified as corresponding to a user, and to fill such detected holes. Additionally, embodiments described herein can be used to produce a low resolution version of a subset of pixels that has been specified as corresponding to a user, so that when an image including a representation of the user is displayed, the image respects the shape of the user, yet is not a mirror image of the user. Further, embodiments described herein can be used to identify pixels, of a subset of pixels specified as corresponding to the user, that likely correspond to a floor supporting the user. This enables the removal of the pixels, identified as likely corresponding to the floor, from the subset of pixels specified as corresponding to the user.

Abstract: A facial skin mask may be generated based on isolating a head part in a captured image, removing a first pixel that is indicative of non-skin from the head part in the captured image, and removing a second pixel that is indicative of having a high velocity from the head part in the captured image. Heart rate may be detected based on the change of color of the pixels of the generated facial skin mask.

Abstract: A facial skin mask may be generated based on isolating a head part in a captured image, removing a first pixel that is indicative of non-skin from the head part in the captured image, and removing a second pixel that is indicative of having a high velocity from the head part in the captured image. Heart rate may be detected based on the change of color of the pixels of the generated facial skin mask.

Abstract: Embodiments described herein use depth images to extract user behavior, wherein each depth image specifies that a plurality of pixels correspond to a user. In certain embodiments, one or more average extremity positions of a user, which can also be referred to as average positions of extremity blobs, are extracted from a depth image. An application is then updated based on the average positions of extremity blobs.

Abstract: An active illumination range camera that acquires a range and a picture image of a scene and provides a reflectance for a feature in the scene responsive to a distance for the feature provided by the range image, a registered irradiance for the feature provided by the picture image and registered irradiance for a region of a calibration surface corresponding to the feature provided by an image of the calibration surface acquired by the range camera.

Abstract: A sequence of images is processed to interpret movements of a user. The user's contour and center of gravity are determined and tracked. Based on points of contact between the user and the environment, and upon tracked movement of the center of gravity, forces impressed by the user upon the points of contact with the environment may be deduced by constraint analysis. This center-of-mass model of user movements may be used in conjunction with a skeletal model of the user to provide verification of the validity of the skeletal model. The center-of-mass model may also be used alternatively with the skeletal model fails during those times when use of the skeletal model is problematic.

Abstract: Aspects described herein include a computer-implemented method for detecting heart rate signals. The method includes a step of capturing a first image and a second image of a region of interest. The second image is aligned with the first image in a first spectrum that is insensitive to a characteristic to obtain a correction. Then, a correction based upon the above-mentioned alignment is applied to the second image in a second spectrum that is sensitive to the characteristic. Additional aspects described an image capturing device and a computer-implemented method for updating a user-interactive activity.

Abstract: A facial skin mask may be generated based on isolating a head part in a captured image, removing a first pixel that is indicative of non-skin from the head part in the captured image, and removing a second pixel that is indicative of having a high velocity from the head part in the captured image.

Abstract: Embodiments described herein use depth images to extract user behavior, wherein each depth image specifies that a plurality of pixels correspond to a user. In certain embodiments, information indicative of an angle and/or curvature of a user's body is extracted from a depth image. This can be accomplished by fitting a curve to a portion of a plurality of pixels (of the depth image) that correspond to the user, and determining the information indicative of the angle and/or curvature of the user's body based on the fitted curve. An application is then updated based on the information indicative of the angle and/or curvature of the user's body. In certain embodiments, one or more average extremity positions of a user, which can also be referred to as average positions of extremity blobs, are extracted from a depth image. An application is then updated based on the average positions of extremity blobs.

Abstract: Embodiments described herein use depth images to extract user behavior, wherein each depth image specifies that a plurality of pixels correspond to a user. In certain embodiments, information indicative of an angle and/or curvature of a user's body is extracted from a depth image. This can be accomplished by fitting a curve to a portion of a plurality of pixels (of the depth image) that correspond to the user, and determining the information indicative of the angle and/or curvature of the user's body based on the fitted curve. An application is then updated based on the information indicative of the angle and/or curvature of the user's body. In certain embodiments, one or more average extremity positions of a user, which can also be referred to as average positions of extremity blobs, are extracted from a depth image. An application is then updated based on the average positions of extremity blobs.

Abstract: Embodiments described herein can be used to detect holes in a subset of pixels of a depth image that has been specified as corresponding to a user, and to fill such detected holes. Additionally, embodiments described herein can be used to produce a low resolution version of a subset of pixels that has been specified as corresponding to a user, so that when an image including a representation of the user is displayed, the image respects the shape of the user, yet is not a mirror image of the user. Further, embodiments described herein can be used to identify pixels, of a subset of pixels specified as corresponding to the user, that likely correspond to a floor supporting the user. This enables the removal of the pixels, identified as likely corresponding to the floor, from the subset of pixels specified as corresponding to the user.

Abstract: Embodiments described herein use depth images to extract user behavior, wherein each depth image specifies that a plurality of pixels correspond to a user. In certain embodiments, information indicative of an angle and/or curvature of a user's body is extracted from a depth image. This can be accomplished by fitting a curve to a portion of a plurality of pixels (of the depth image) that correspond to the user, and determining the information indicative of the angle and/or curvature of the user's body based on the fitted curve. An application is then updated based on the information indicative of the angle and/or curvature of the user's body. In certain embodiments, one or more average extremity positions of a user, which can also be referred to as average positions of extremity blobs, are extracted from a depth image. An application is then updated based on the average positions of extremity blobs.

Abstract: Embodiments described herein can be used to detect holes in a subset of pixels of a depth image that has been specified as corresponding to a user, and to fill such detected holes. Additionally, embodiments described herein can be used to produce a low resolution version of a subset of pixels that has been specified as corresponding to a user, so that when an image including a representation of the user is displayed, the image respects the shape of the user, yet is not a mirror image of the user. Further, embodiments described herein can be used to identify pixels, of a subset of pixels specified as corresponding to the user, that likely correspond to a floor supporting the user. This enables the removal of the pixels, identified as likely corresponding to the floor, from the subset of pixels specified as corresponding to the user.

Abstract: Embodiments described herein use depth images to extract user behavior, wherein each depth image specifies that a plurality of pixels correspond to a user. A depth-based center-of-mass position is determined for the plurality of pixels that correspond to the user. Additionally, a depth-based inertia tensor can also be determined for the plurality of pixels that correspond to the user. In certain embodiments, the plurality of pixels that correspond to the user are divided into quadrants and a depth-based quadrant center-of-mass position is determined for each of the quadrants. Additionally, a depth-based quadrant inertia tensor can be determined for each of the quadrants. Based on one or more of the depth-based center-of-mass position, the depth-based inertial tensor, the depth-based quadrant center-of-mass positions or the depth-based quadrant inertia tensors, an application is updated.