13915681
Capturing and animating skin deformation in human motion
During dynamic activities, the surface of the human body moves in many subtle but visually significant ways: bending, bulging, jiggling, and stretching. We present a technique for capturing and animating those motions using a commercial motion capture system and approximately 350 markers. Although the number of markers is significantly larger than that used in conventional motion capture, it is only a sparse representation of the true shape of the body. We supplement this sparse sample with a detailed, actor-specific surface model. The motion of the skin can then be computed by segmenting the markers into the motion of a set of rigid parts and a residual deformation (approximated first as a quadratic transformation and then with radial basis functions). We demonstrate the power of this approach by capturing flexing muscles, high frequency motions, and abrupt decelerations on several actors. We compare these results both to conventional motion capture and skinning and to synchronized video of the actors.
17481727
Strain analysis and visualization: left ventricle of a heart
Abstract Clinical utility of computational models is crucial in the applications of medical data visualization. Previously we have developed a new class of volumetric models whose parameters are functions in conjunction with physically based deformable modeling framework, and have applied the technique to estimate the left ventricular (LV) wall motion. We have successfully showed that the model parameter functions characterize the LV motion of normal and abnormal states and that no further non-trivial post-processing is required for anatomically meaningful interpretation. In an effort to evaluate the LV model, this paper presents a method and results from a strain analysis based on the nodal displacements of the deformable LV model. Furthermore, in order to visualize the local quantities on the volumetric model for an effective analysis, we also developed a methodology to assist in assessing the cardiac function utilizing principal strains, Von-Mises’ yield criteria, and a smoothing filter. Each strain tensor component was in the range of values observed in other reported studies. The application of a smoothing filter on the model improved in visualizing the overall trend of each strain variation. With our platform for a comprehensive strain analysis, we have augmented a clinical utility to the deformable models with parameter functions.
6023163
Automatic 3D model reconstruction using voxel coding and pose integration
Automatic reconstruction of a complete 3D model of a complex object is presented. The complete 3D model is reconstructed by integrating two 3D models which are reconstructed from different poses of the object. For each pose of the object, a 3D model is reconstructed by combining stereo image analysis, shape from silhouettes, and a volumetric integration technique. Stereo image analysis and shape from silhouettes techniques complement each other to reconstruct an accurate and noise-resistant 3D model. For a reliable volumetric integration of multiple partial shapes, a voxel coding technique is introduced. The voxel coding technique facilitates a selection of consistent partial shapes for shape integration. In order to reconstruct all visible surfaces of a complex object with concavities and holes, two 3D models from different poses of the object are reconstructed and integrated to obtain the complete 3D model. A voxel coding technique is again used during pose integration. Experimental results on a real object demonstrate that our approach has advantages and is effective.
36047409
A Comparison of Scalable Labeling Schemes for Detecting Races in OpenMP Programs
Detecting races is important for debugging shared-memory parallel programs, because the races result in unintended nondeterministic executions of the program. On-the-fly technique to detect races uses a scalable labeling scheme which generates concurrency information of parallel threads without any globally-shared data structure. Two efficient schemes of scalable labeling, BD Labeling and NR Labeling, show the similar complexities in space and time, but their actual efficiencies have been compared empirically in no literature to the best of our knowledge. In this paper, we empirically compare these two labeling schemes by monitoring a set of OpenMP kernel programs with nested parallelism. The empirical results show that NR Labeling is more efficient than BD Labeling by at least 1.5 times in generating the thread labels, and by at least 3.5 times in using the labels to detect races in the kernel programs.
34356748
Model-Based Human Motion Capture from Monocular Video Sequences
Generating motion and capturing motion of an articulated body for computer animation is an expensive and time-consuming task. Conventionally, animators manually generate intermediate frames between key frames, but this task is very labor-intensive. This paper presents a model-based singularity-free automatic-initialization approach to capturing human motion from widely-available, static background monocular video sequences. A 3D human body model is built and projected on a 2D projection plane to find the best fit with the foreground image silhouette. We convert the human motion capture problem into two types of parameter optimization problems: static optimization and dynamic optimization. First, we determine each model body configuration using static optimizations for every input image. Then, to obtain better description of motion, the results from all static optimizations are fed into a dynamic optimization process where the entire sequence of motion is considered for the user-specified motion. The user-specified motion is defined by the user and the final form of the motion they want. A cost function for static optimization is used to estimate the degree of overlapping between the foreground input image silhouette and a projected 3D model body silhouette. The overlapping is computed using computational geometry by converting a set of pixels from the image domain to a polygon in the real projection plane domain. A cost function for dynamic optimization is the user-specified motion based on the static optimization results as well as image fitting. Our method is used to capture various human motions: walking, pushing, kicking, and handshaking.
310444
Managing energy-performance tradeoffs for multithreaded applications on multiprocessor architectures
In modern computers, non-performance metrics such as energy consumption have become increasingly important, requiring tradeoff with performance. A recent work has proposed performance-guaranteed energy management, but it is designed specifically for sequential applications and cannot be used to a large class of multithreaded applications running on high end computers and data servers.
 To address the above problem, this paper makes the first attempt to provide performance-guaranteed energy management for multithreaded applications on multiprocessor architectures. We first conduct a comprehensive study on the effects of energy adaptation on thread synchronizations and show that a multithreaded application suffers from not only local slowdowns due to energy adaptation, but also significant slowdowns propagated from other threads because of synchronization. Based on these findings, we design three Synchronization-Aware (SA) algorithms, LWT (Lock Waiting Time-based), CSL (Critical Section Length-based) and ODP (Operation Delay Propagation-based) algorithms, to estimate the energy adaptation-induced slowdowns on each thread. The local slowdowns are then combined across multiple threads via three aggregation methods (MAX, AVG and SUM) to estimate the overall application slowdown.
 We evaluate our methods using a large multithreaded commercial application, IBM DB2 with industrial-strength online transaction processing (OLTP) workloads, and six SPLASH parallel scientific applications. Our experimental results show that LWT combined with the MAX aggregation method not only controls the performance slow down within the specified limits but also conserves the most energy.
42767167
Location Discovery in Ad Hoc Sensor Networks