Intel Corporation

Alon Lerner

Shahar Fleishman

Maoz Madmony

Mark Kliger

Identifying a local coordinate system is described for gesture recognition. In one example, a method includes receiving a gesture from a user across a horizontal axis at a depth camera, determining a horizontal vector for the user based on the received user gesture, determining a vertical vector; and determining a rotation matrix to convert positions of user gestures received by the camera to a frame of reference of the user.

Gesture recognition based on transformation between a coordinate system of a user and a coordinate system of a camera

Hand dimensions are determined for hand and gesture recognition with a computing interface. An input sequence of frames is received from a camera. Frames of the sequence are identified in which a hand is recognized. Points are identified in the identified frames corresponding to features of the recognized hand. A value is determined for each of a set of different feature lengths of the recognized hand using the identified points for each identified frame. Each different feature length value is collected for the identified frames independently of each other feature length value. Each different feature length value is analyzed to determine an estimate of each different feature length, and the estimated feature lengths are applied to a hand tracking system, the hand tracking system for applying commands to a computer system.

Determination of hand dimensions for hand and gesture recognition with a computing interface

Identifying a local coordinate system for gesture recognition

Techniques related to pose estimation for an articulated body are discussed. Such techniques may include extracting, segmenting, classifying, and labeling blobs, generating initial kinematic parameters that provide spatial relationships of elements of a kinematic model representing an articulated body, and refining the kinematic parameters to provide a pose estimation for the articulated body.

Detection, tracking, and pose estimation of an articulated body

Techniques related to non-rigid transformations for articulated bodies are discussed. Such techniques may include repeatedly selecting target positions for matching a kinematic model of an articulated body, generating virtual end-effectors for the kinematic model and corresponding to the target positions, generating an inverse kinematics problem including a Jacobian matrix, and determining a change in kinematic model parameters based on the inverse kinematics problem until a convergence is attained.

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Holon, Israel

Alon Lerner