Editorial Issue 28.1

Abstract

This issue contains five papers. In the first paper, Angel Zaldivar Pino, Manuel Gonzalez Bedia, and Francisco J. Seron, from Universidad Zaragoza, Spain, present a simulation framework in which the agents are endowed with a sensing device, an oscillator network as controller, and actuators to interact with the environment. The perception device is designed as an optic array emulating the principles of the animal retina, which assimilates stimuli resembling optic flow to be captured from the environment. The controller modulates informational variables to action variables in a sensory motor flow. Their approach is based on the Kuramoto model that describes mathematically a network of coupled phase oscillators and the use of evolutionary algorithms, which is proved to be capable of synthesizing minimal synchronization strategies based on the dynamical coupling between agents and environment. In the second paper, Congkun Chen, Yun Sheng, Fang Li, Guixu Zhang, from East China Normal University, Shanghai, China, and Hassan Ugail, from University of Bradford, UK, propose an extension of the use of the partial differential equation (PDE) method to head visualization with CT data and show how the two primary medical visualization means, surface reconstruction, and volume rendering can be integrated into one single framework through PDEs. Their scheme first performs head segmentation from CT slices using a variational approach; with the extracted boundary conditions, head surface reconstruction is then executed. Since only a few slices are used, their method can perform head surface reconstruction more efficiently in both computational time and storage cost than the widely used marching cubes algorithm. By elaborately introducing a third parameter ω to the PDE method, a solid head can be created, based on which the head volume is subsequently rendered with 3-D texture mapping. In the third paper, Francis Laclé, Utrecht University, the Netherlands, and Nicolas Pronost, Université Claude Bernard, Lyon, France, focus on combining, by a controllable enhancement process, a functional and biomechanical model of musculotendon units with its high-resolution geometrical counterpart. The method was developed in order to be invariant to spatial and polygonal configurations and to be scalable in both longitudinal and latitudinal directions. Results with 48 musculotendon units for the lower body show a drop of 84% with respect to the number of vertices when compared to the high-resolution model, while maintaining the functional information. A real-time simulation experiment resulted in a runtime of 135 Hz. Sergio Orts-Escolano, from University of Alicante, Spain, Johannes Bastiaan Boom, Xin Xin Ning, Steven McDonagh, Peter Sandilands, and Robert B. Fisher, from University of Edinburgh, UK, propose in the fourth paper, the first hybrid CPU-GPU based method for estimating a point light source position in a scene recorded by an RGB-D camera. The image and depth information from the Kinect is enough to estimate a light position in a scene, which allows for the rendering of synthetic objects into a scene that appear realistic enough for augmented reality purposes. This method does not require a light probe or other physical device. To make this method suitable for augmented reality, the authors developed a hybrid implementation that performs light estimation in less than 1 s. By rendering synthetic objects into the recorded scene, they illustrate that this accuracy is good enough for the rendered objects to look realistic. Finally, Jorge Eduardo Ramirez Flores and Antonio Susin Sanchez, from Universitat Politecnica de Catalunya, Barcelona, Spain, present an approach based on mesh segmentation for skinning and skeleton-driven computer animation. They propose a novel and fast method, based in watershed segmentation to deal with characters in T-Pose and arbitrary poses; they also introduce a simple weight assign algorithm based in the rigid skinning obtained with the segmentation algorithm for the linear blend skinning (LBS) deformation method. They ultimately propose a modified version of the LBS that avoids the loss of volume in twist rotations using the segmentation stage output values.