Abstract: For artificial reality (XR) applications that need a guardian, aspects of the present disclosure can automatically determine where boundaries should be set in the real-world environment. Using a machine learning model, the automatic boundary system can detect the floor plane, then generate a height map of the real-world environment with the floor at zero. The height map can include positive heights (e.g., objects on the floor) and negative heights (e.g., downward leading stairs). The automatic boundary system can then generate a boundary for the area based on the detected heights by: applying thresholds to disregard objects at certain heights, applying thresholds to disregard open areas at certain widths, excluding oddly shaped areas that would constantly trigger the boundary if the user were nearby, etc. The user can further manually adjust the generated boundary in both directions (e.g., bringing it closer or further from the user).

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A determinate castor is provided. Also provided are methods of generating and using same as well as products thereof.

Abstract: 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.

Abstract: A determinate castor is provided. Also provided are methods of generating and using same as well as products thereof.

Abstract: 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.

Abstract: 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.

Abstract: Shadow regions in image depth data that are caused by multiple image sensors are detected. In one example a region of a row of pixel depth data in a row of pixels from a depth image is identified. A first valid pixel on a first side of the identified region is un-projected into a three-dimensional space to determine first point P1. A first vector is determined from the position C2 of the second camera to the first point. A second valid pixel on a second side of the identified region is un-projected into a three-dimensional space to determine second point P2. A second vector is determined from the position C2 of the second camera to the second point. An angle is determined between the first vector and the second vector and compared to a threshold. The missing region is classified as a shadow region if the angle is less than the threshold.

Abstract: Hand skeletons are compared to a hand image and selected. The hand skeletons are used for hand and gesture recognition with a computing interface. In one example, the method includes projecting points of a generated hand skeleton onto a received hand image, classifying the skeleton points as inside or outside the hand image, quantifying the comparison to generate a comparison quantity using a comparison function distance measurement, the comparison function distance measurement comprising an outside skeleton distance that includes a sum of distances from each outside skeleton point to a nearest inside skeleton point, applying the comparison function quantity to select the generated hand skeleton as a best match, and applying the selected hand skeleton to generate a command to a computer system command interface.

Abstract: 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.

Abstract: A determinate castor is provided. Also provided are methods of generating and using same as well as products thereof.

Abstract: 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.

Abstract: 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.

Abstract: Technologies for learning body part geometry are described. In some embodiments the technologies include systems, methods and computer readable medium for extracting biometric information from a body part of a user, such as the user's hand. In some instances the extraction is performed with the aid of a calibrated computer model of the body part in question. Body part information may be saved in a data structure for use as a biometric template. The Biometric authentication processes utilizing the technologies are also described.

Abstract: A polyploid castor plant being at least as fertile as a diploid castor plant isogenic to the polyploid castor plant when grown under similar conditions.

Abstract: A rapeseed plant having a multiplied genome being at least as fertile as a euploid rapeseed plant isogenic to the genomically multiplied plant grown under similar conditions.

Abstract: A Durum wheat plant having a partially or fully multiplied genome being at least as fertile as a tetraploid Durum wheat (Triticum Durum) plant isogenic to said genomically multiplied Durum wheat plant when grown under the same conditions and being of the same developmental stage is provided. Also provided are methods of generating and using same as well as products generated therefrom.