Two-frame 3D particle tracking

3d Head Tracking by Particle Filters

In this paper, we propose a particle filter framework for 3D tracking of heads and faces in monocular video sequences. We propose two different approaches. The first approach utilizes a statistical facial texture model as an observation likelihood. The second approach utilizes a deterministic facial texture which is built on-line. The developed approaches have been successfully tested on severa...

Agnostic Tracking: Nanoscale, High Bandwidth, 3d Particle Tracking for Biology

Tracking Growing Axons by Particle Filtering in 3D + t Fluorescent Two-Photon Microscopy Images

Analyzing the behavior of axons in the developing nervous systems is essential for biologists to understand the biological mechanisms underlying how growing axons reach their target cells. The analysis of the motion patterns of growing axons requires detecting axonal tips and tracking their trajectories within complex and large data sets. When performed manually, the tracking task is arduous an...

3D Head Tracking using the Particle Filter with Cascaded Classifiers

We propose a method for real-time people tracking using multiple cameras. The particle filter framework is known to be effective for tracking people, but most of existing methods adopt only simple perceptual cues such as color histogram or contour similarity for hypothesis evaluation. To improve the robustness and accuracy of tracking more sophisticated hypothesis evaluation is indispensable. W...

3D particle tracking velocimetry using dynamic discrete tomography

Particle tracking velocimetry in 3D is becoming an increasingly important imaging tool in the study of fluid dynamics and combustion as well as plasmas. We introduce a dynamic discrete tomography algorithm for reconstructing particle trajectories from projections. The algorithm is efficient for data from two projection directions and exact in the sense that it finds a solution consistent with t...