Biomedical subjects

Pascal Fua

Publications and source records attributed to Pascal Fua.

4 recordsLinked to original sources

PubMed2006

Estimation and visualization of sagittal kinematics of lower limbs orientation using body-fixed sensors.

A new method of estimating lower limbs orientations using a combination of accelerometers and gyroscopes is presented. The model is based on estimating the accelerations of ankle and knee joints by placing virtual sensors at the centers of rotation. The proposed technique considers human locomotion and biomechanical constraints, and provides a solution to fusing the data of gyroscopes and accelerometers that yields stable and drift-free estimates of segment orientation. The method was validated by measuring lower limb motions of eight subjects, walking at three different speeds, and comparing the results with a reference motion measurement system. The results are very close to those of the reference system presenting very small errors (Shank: rms = 1.0, Thigh: rms = 1.6 degrees) and excellent correlation coefficients (Shank: r = 0.999, Thigh: r = 0.998). Technically, the proposed ambulatory system is portable, easily mountable, and can be used for long-term monitoring without hindrance to natural activities. Finally, a gait analysis tool was designed to visualize the motion data as synthetic skeletons performing the same actions as the subjects.

Acceleration↗

PubMed2006

Keypoint recognition using randomized trees.

In many 3D object-detection and pose-estimation problems, runtime performance is of critical importance. However, there usually is time to train the system, which we will show to be very useful. Assuming that several registered images of the target object are available, we developed a keypoint-based approach that is effective in this context by formulating wide-baseline matching of keypoints extracted from the input images to those found in the model images as a classification problem. This shifts much of the computational burden to a training phase, without sacrificing recognition performance. As a result, the resulting algorithm is robust, accurate, and fast-enough for frame-rate performance. This reduction in runtime computational complexity is our first contribution. Our second contribution is to show that, in this context, a simple and fast keypoint detector suffices to support detection and tracking even under large perspective and scale variations. While earlier methods require a detector that can be expected to produce very repeatable results, in general, which usually is very time-consuming, we simply find the most repeatable object keypoints for the specific target object during the training phase. We have incorporated these ideas into a real-time system that detects planar, nonplanar, and deformable objects. It then estimates the pose of the rigid ones and the deformations of the others.

Algorithms↗

PubMed2006

Implicit meshes for surface reconstruction.

Deformable 3D models can be represented either as traditional explicit surfaces, such as triangulated meshes, or as implicit surfaces. Explicit surfaces are widely accepted because they are simple to deform and render, but fitting them involves minimizing a nondifferentiable distance function. By contrast, implicit surfaces allow fitting by minimizing a differentiable algebraic distance, but are harder to meaningfully deform and render. Here, we propose a method that combines the strength of both approaches. It relies on a technique that can turn a completely arbitrary triangulated mesh, such as one taken from the Web, into an implicit surface that closely approximates it and can deform in tandem with it. This allows both automated algorithms to take advantage of the attractive properties of implicit surfaces for fitting purposes and people to use standard deformation tools they feel comfortable for interaction and animation purposes. We demonstrate the applicability of our technique to modeling the human upper-body, including face, neck, shoulders, and ears, from noisy stereo and silhouette data.

Algorithms↗

PubMed2004

Stable real-time 3D tracking using online and offline information.

We propose an efficient real-time solution for tracking rigid objects in 3D using a single camera that can handle large camera displacements, drastic aspect changes, and partial occlusions. While commercial products are already available for offline camera registration, robust online tracking remains an open issue because many real-time algorithms described in the literature still lack robustness and are prone to drift and jitter. To address these problems, we have formulated the tracking problem in terms of local bundle adjustment and have developed a method for establishing image correspondences that can equally well handle short and wide-baseline matching. We then can merge the information from preceding frames with that provided by a very limited number of keyframes created during a training stage, which results in a real-time tracker that does not jitter or drift and can deal with significant aspect changes.

Algorithms↗