Motion correction for separate mandibular and cranial movements in cone beam CT reconstructions.

Background: Patient motions are a repeatedly reported phenomenon in oral and maxillofacial cone beam CT scans, leading to reconstructions of limited usability. In certain cases, independent movements of the mandible induce unpredictable motion patterns. Previous motion correction methods are not able to handle such complex cases of patient movements.

Projection-based improvement of 3D reconstructions from motion-impaired dental cone beam CT data.

Purpose: Computed tomography (CT) and, in particular, cone beam CT (CBCT) have been increasingly used as a diagnostic tool in recent years. Patient motion during acquisition is common in CBCT due to long scan times. This results in degraded image quality and may potentially increase the number of retakes.

A method for automatic forensic facial reconstruction based on dense statistics of soft tissue thickness.

In this paper, we present a method for automated estimation of a human face given a skull remain. Our proposed method is based on three statistical models. A volumetric (tetrahedral) skull model encoding the variations of different skulls, a surface head model encoding the head variations, and a dense statistic of facial soft tissue thickness (FSTT).

A Region-Based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking.

We propose an algorithm for real-time 6DOF pose tracking of rigid 3D objects using a monocular RGB camera. The key idea is to derive a region-based cost function using temporally consistent local color histograms. While such region-based cost functions are commonly optimized using first-order gradient descent techniques, we systematically derive a Gauss-Newton optimization scheme which gives rise to drastically faster convergence and highly accurate and robust tracking performance.

Ultrahigh temporal resolution of visual presentation using gaming monitors and G-Sync.

Vision unfolds as an intricate pattern of information processing over time. Studying vision and visual cognition therefore requires precise manipulations of the timing of visual stimulus presentation. Although standard computer display technologies offer great accuracy and precision of visual presentation, their temporal resolution is limited.