A markerless method is described for tracking the motion of subjects in a three dimensional environment using a model based on linked kinematic chains. The invention is suitable for tracking robotic, animal or human subjects in real-time using a single computer with inexpensive video equipment, and does not require the use of markers or specialized clothing. A simple model of rigid linked segments is constructed of the subject and tracked using three dimensional volumetric data collected by a multiple camera video imaging system. A physics based method is then used to compute forces to align the model with subsequent volumetric data sets in real-time. The method is able to handle occlusion of segments and accommodates joint limits, velocity constraints, and collision constraints and provides for error recovery. The method further provides for elimination of singularities in Jacobian based calculations, which has been problematic in alternative methods.
A method of providing a volumetric representation of a three dimensional object includes defining a plurality of voxels in a three dimensional space, categorizing voxels as foreground or background according to at least one silhouette image of the object, foreground voxels being assigned a first binary value, and background voxels being assigned a second binary value, and assigning to at least some voxels a value intermediate between the first and second binary values.
Disclosed is a method and system for efficiently and accurately tracking three-dimensional (3D) human motion from a two-dimensional (2D) video sequence, even when self-occlusion, motion blur and large limb movements occur. In an offline learning stage, 3D motion capture data is acquired and a prediction model is generated based on the learned motions. A mixture of factor analyzers acts as local dimensionality reducers. Clusters of factor analyzers formed within a globally coordinated low-dimensional space makes it possible to perform multiple hypothesis tracking based on the distribution modes. In the online tracking stage, 3D tracking is performed without requiring any special equipment, clothing, or markers. Instead, motion is tracked in the dimensionality reduced state based on a monocular video sequence.
A method of determining a three-dimensional velocity field in a volume having particles, the particles within the volume being excited to radiate by illuminating the volume, including two or more cameras simultaneously capturing images of the observation volume at two different instants of time, the observation volume being divided into small volume elements (voxels), each voxel being projected onto image points of the cameras, the intensity of all the voxels being reconstructed from the measured intensity of the respective associated image points, a plurality of voxels being combined to form an interrogation volume, and a displacement vector being determined by a three-dimensional cross correlation of the two interrogation volumes.
In one aspect, a method and apparatus for determining a value for at least one parameter of a configuration of a model associated with structure of which view data has been obtained including detecting at least one feature in the view data, and determining the value for the at least one parameter of the configuration of the model based at least in part on the at least one feature. In another aspect, a method and apparatus for detecting at least one blood vessel from object view data obtained from a scan of the at least one blood vessel including generating a model of the at least one blood vessel, the model having a plurality of parameters describing a model configuration, determining a hypothesis for the model configuration based, at least in part, on at least one feature detected in the object view data, and updating the model configuration according to a comparison with the object view data to arrive at a final model configuration, so that the final model configuration represents the at least one blood vessel.
