107 results about "Pose tracking" patented technology

Dense range data obtained at real-time rates is employed to estimate the pose of an articulated figure. In one approach, the range data is used in combination with a model of connected patches. Each patch is the planar convex hull of two circles, and a recursive procedure is carried out to determine an estimate of pose which most closely correlates to the range data. In another aspect of the invention, the dense range data is used in conjunction with image intensity information to improve pose tracking performance. The range information is used to determine the shape of an object, rather than assume a generic model or estimate structure from motion. In this aspect of the invention, a depth constraint equation, which is a counterpart to the classic brightness change constraint equation, is employed. Both constraints are used to jointly solve for motion estimates.

The invention discloses a Kinect-based robot self-positioning method. The method includes the following steps that: the RGB image and depth image of an environment are acquired through the Kinect, and the relative motion of a robot is estimated through the information of visual fusion and a physical speedometer, and pose tracking can be realized according to the pose of the robot at a last time point; depth information is converted into three-dimensional point cloud, and a ground surface is extracted from the point cloud, and the height and pitch angle of the Kinect relative to the ground surface are automatically calibrated according to the ground surface, so that the three-dimensional point cloud can be projected to the ground surface, and therefore, two-dimensional point cloud similar to laser data can be obtained, and the two-dimensional point cloud is matched with pre-constructed environment raster map, and thus, accumulated errors in a robot tracking process can be corrected, and the pose of the robot can be estimated accurately. According to the Kinect-based robot self-positioning method of the invention, the Kinect is adopted to replace laser to perform positioning, and therefore, cost is low; image and depth information is fused, so that the method can have high precision; and the method is compatible with a laser map, and the mounting height and pose of the Kinect are not required to be calibrated in advance, and therefore, the method is convenient to use, and requirements for autonomous positioning and navigation of the robot can be satisfied.

The invention provides an unscented Kalman filter-based method for tracking an inertial pose according to acceleration compensation, which is used for an inertial measurement unit integrating a three-axis micro-gyroscope, a three-axis micro-accelerometer and a three-axis magnetoresistive sensor, and realizes pose tracking estimation on a device carrier by using rotary angular velocity vectors, acceleration vectors and magnetic field sensor vectors which are detected by the device by means of filter technology. The method comprises the following steps: 1) treating the acceleration vectors as combination of the acceleration vectors and gravity acceleration vectors of the device carrier self, and constructing observation equations respectively for amplitude and normalized direction vectors of the acceleration vectors and the gravity acceleration vectors; 2) describing quaternion, accumulated error vectors of the gyroscope and the acceleration vectors of the device carrier self by using the pose to construct a system state vector; and 3) realizing a filter estimating process of the system by using the unscented Kalman filter technology because of nonlinearity of the observation equations. Compared with the conventional method ignoring the acceleration of the carrier self, the method not only can provide a more accurate estimation result, but also widens the application range of the system.

A reference in an unknown environment is generated on the fly for positioning and tracking. The reference is produced in a top down process by capturing an image of a planar object with a predefined geometric shape, detecting edge pixels of the planar object, then detecting a plurality of line segments from the edge pixels. The plurality of line segments may then be used to detect the planar object in the image based on the predefined geometric shape. An initial pose of the camera with respect to the planar object is determined and tracked using the edges of the planar object.

The invention discloses a method for three-dimensional human pose estimation, which can realize the real-time and high-precision 3D human pose estimation without high configuration hardware support and precise human body model. In this method for three-dimensional human pose estimation, including the following steps: (1) establishing a three-dimensional human body model matching the object, which is a cloud point human body model of visible spherical distribution constraint. (2) Matching and optimizing between human body model for human body pose tracking and depth point cloud. (3) Recovering for pose tracking error based on dynamic database retrieval.

A method for obtaining a refined pose for a 3D sensor for online 3D modeling of a surface geometry of an object, the pose encompassing six degrees of freedom (DOF) including three translation parameters and three orientation parameters, the method comprising: providing the 3D sensor, the 3D sensor being adapted to capture 3D point measurements of the surface of the object from a viewpoint; providing a geometry model of at least part of the surface; observing a portion of the surface of the object with the 3D sensor; measuring an initialization pose for the 3D sensor by at least one of positioning device pose measurement, predicted pose tracking and target observation; finding a best fit arrangement of the 3D point measurements in the geometry model using the initialization pose; generating the refined pose for the 3D sensor using the best fit arrangement.

The invention relates to a real-time pose tracking method based on a target three-dimensional model. According to the method, based on a three-dimensional model of a target, contour features are utilized to establish a contour component model, and a contour is divided into a plurality of local contour sections according to the local contour recognition degree; For each contour segment, two dimensional-three dimensional correspondence is established in a gradient domain based on a phase matching criterion; a wrong matching pair is established by utilizing a geometrical relationship among all parts of the rigid body target; based on the established two dimensional-three dimensional matching pair, a pose parameter is solved through an RPNP algorithm, the whole process is iterated until convergence, and target pose tracking in the sequence image is realized. The algorithm is simple and clear in step and easy to apply, and drift-free tracking in the whole process can be achieved due to introduction of the three-dimensional model of the target.

A reference in an unknown environment is generated on the fly for positioning and tracking. The reference is produced in a top down process by capturing an image of a planar object with a predefined geometric shape, detecting edge pixels of the planar object, then detecting a plurality of line segments from the edge pixels. The plurality of line segments may then be used to detect the planar object in the image based on the predefined geometric shape. An initial pose of the camera with respect to the planar object is determined and tracked using the edges of the planar object.

Methods and systems for registering a manipulator assembly and independently positionable surgical table are provided herein. In one aspect, methods include reading a fiducial marker on the surgical table with a sensor associated with the manipulator assembly and localizing the manipulator assembly and surgical table with respect to a common reference frame. Methods may further include translating a 3D configuration of the surgical table to a 2D frame of reference so as to estimate a 3D pose of the surgical table relative the manipulator assembly for use in coordinating movements therebetween.

The embodiment of the invention discloses a surgery navigation image display method and system based on augmented reality. When a mark point on a marker is blocked, a preset algorithm model is adoptedto process a gesture rotation matrix of the marker on a current moment, a three-dimensional space coordinate of the mark point on the marker and three-dimensional space displacement between the markpoint and an initially defined original point to obtain the three-dimensional space coordinate of the original point at the current moment; according to the position relationship between a target object and the initially defined original point and the three-dimensional space coordinate of the original point at the current moment, the position information of the target object at the current momentis obtained; finally, gesture information and position information are used as a pose tracking result of the target object, the pose tracking result is combined with a real scene to generate a surgerynavigation image. By use of the scheme, the position accuracy of a surgery tool in the real scene in the surgery navigation image can be improved.

This application discloses a repositioning method performed by an electronic device in a camera pose tracking process, belonging to the field of augmented reality (AR). The method includes: obtaining a current image acquired by the camera after an ith anchor image in a plurality of anchor images; selecting a target keyframe from a keyframe database according to Hash index information in a case that the current image satisfies a repositioning condition; performing second repositioning on the current image relative to the target keyframe; and calculating a camera pose parameter of a camera during acquisition of the current image according to a positioning result of the first repositioning and a positioning result of the second repositioning. In a case that there are different keyframes covering a surrounding area of a camera acquisition scene, it is highly probable that repositioning can succeed, thereby improving the success probability of a repositioning process.