Learn More
The availability of accurate depth cameras have made real-time human pose estimation possible; however, there are still demands for faster algorithms on low power processors. This paper introduces 1000 frames per second pose estimation method on a single core CPU. A large computation gain is achieved by random walk sub-sampling. Instead of training trees(More)
In this paper, we propose a nonrigid registration method using the Markov Random Field (MRF) model with a higher-order spatial prior. The registration is designed as finding a set of discrete displacement vectors on a deformable mesh, using the energy model defined by label sets relating to these vectors. This work provides two main ideas to improve the(More)
In this paper a method to extract cerebral arteries from computed tomographic angiography (CTA) is proposed. Since CTA shows both bone and vessels, the examination of vessels is a difficult task. In the upper part of the brain, the arteries of main interest are not close to bone and can be well segmented out by thresholding and simple connected-component(More)
In this paper a method to extract cerebral arterial segments from CT angiography (CTA) is proposed. The segmentation of cerebral arteries in CTA is a challenging task mainly due to bone contact and vein contamination. The proposed method considers a vessel segment as an ellipse travelling in three-dimensional (3D) space and segments it out by tracking the(More)
In this paper, we propose an algorithm to produce 3-D surface model from a set of range data, based on Non-Uniform Rational B-Splines (NURBS) surface tting technique. It is assumed that the range data is initially unorganized and scattered 3-D points, while their connectivity is also unknown. The proposed algorithm is roughly made up of two stages: initial(More)