We propose a new method, based on inertial sensors, to automatically measure at high frequency the durations of the main phases of ski jumping (i.e. take-off release, take-off, and early flight). The kinematics of the ski jumping movement were recorded by four inertial sensors, attached to the thigh and shank of junior athletes, for 40 jumps performed during indoor conditions and 36 jumps in field conditions. An algorithm was designed to detect temporal events from the recorded signals and to estimate the duration of each phase. These durations were evaluated against a reference camera-based motion capture system and by trainers conducting video observations. The precision for the take-off release and take-off durations (indoor < 39 ms, outdoor = 27 ms) can be considered technically valid for performance assessment. The errors for early flight duration (indoor = 22 ms, outdoor = 119 ms) were comparable to the trainers' variability and should be interpreted with caution. No significant changes in the error were noted between indoor and outdoor conditions, and individual jumping technique did not influence the error of take-off release and take-off. Therefore, the proposed system can provide valuable information for performance evaluation of ski jumpers during training sessions.
In this article, we present a parallel prioritized Jacobian-based inverse kinematics algorithm for multithreaded architectures. We solve damped least squares inverse kinematics using a parallel line search by identifying and sampling critical input parameters. Parallel competing execution paths are spawned for each parameter in order to select the optimum that minimizes the error criteria. Our algorithm is highly scalable and can handle complex articulated bodies at interactive frame rates. We show results on complex skeletons consisting of more than 600 degrees of freedom while being controlled using multiple end effectors. We implement the algorithm both on multicore and GPU architectures and demonstrate how the GPU can further exploit fine-grain parallelism not directly available on a multicore processor. Our implementations are 10 to 150 times faster compared to a state-of-the-art serial implementation while providing higher accuracy. We also demonstrate the scalability of the algorithm over multiple scenarios and explore the GPU implementation in detail.
In this paper, we present an interactive motion deformation method to modify animations so that they satisfy a set of prioritized constraints. Our approach successfully handles the problem of retargetting, adjusting a motion, as well as adding significant changes to preexisting animations. We introduce the concept of prioritized constraints to avoid tweaking issues for competing constraints. Each frame is individually and smoothly adjusted to enforce a set of prioritized constraints. The iterative construction of the solution channels the convergence through intermediate solutions, enforcing the highest prioritized constraints first. In addition, we propose a new, simple formulation to control the position of the center of mass so that the resulting motions are physically plausible. Finally, we demonstrate that our method can address a wide range of motion editing problems.
In this paper we present a new method to track bone movements in stereoscopic X-ray image series of the knee joint. The method is based on two different X-ray image sets: a rotational series of acquisitions of the still subject knee that allows the tomographic reconstruction of the three-dimensional volume (model), and a stereoscopic image series of orthogonal projections as the subject performs movements. Tracking the movements of bones throughout the stereoscopic image series means to determine, for each frame, the best pose of every moving element (bone) previously identified in the 3D reconstructed model. The quality of a pose is reflected in the similarity between its theoretical projections and the actual radiographs. We use direct Fourier reconstruction to approximate the three-dimensional volume of the knee joint. Then, to avoid the expensive computation of digitally rendered radiographs (DRR) for pose recovery, we develop a corollary to the 3-dimensional central-slice theorem and reformulate the tracking problem in the Fourier domain. Under the hypothesis of parallel X-ray beams, the heavy 2D-to-3D registration of projections in the signal domain is replaced by efficient slice-tovolume registration in the Fourier domain. Focusing on rotational movements, the translation-relevant phase information can be discarded and we only consider scalar Fourier amplitudes. The core of our motion tracking algorithm can be implemented as a classical frame-wise slice-to-volume registration task. Results on both synthetic and real images confirm the validity of our approach.
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