We introduce a new method for computing optimal path maps on the GPU using OpenGL shaders. Our method explores GPU rasterization as a way to propagate optimal costs on a polygonal 2D environment, producing optimal path maps which can efficiently be queried at run-time. Our method is implemented entirely with GPU shaders, does not require pre-computation, addresses optimal path maps with multiple points and line segments as sources, and introduces a new optimal path map concept not addressed before: maps with weights at vertices representing possible changes in traversal speed. The produced maps offer new capabilities not explored by previous navigation representations and at the same time address paths with global optimality, a characteristic which has been mostly neglected in animated virtual environments. The proposed path maps partition the input environment into the regions sharing a same parent point along the shortest path to the closest source, taking into account possible speed changes at vertices. The proposed approach is particularly suitable for the animation of multiple agents moving toward the entrances or exits of a virtual environment, a situation which is efficiently represented with the proposed path maps.
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http://dx.doi.org/10.1109/TVCG.2019.2904271 | DOI Listing |
Int Conf Indoor Position Indoor Navig
October 2024
Department of Computer Science & Engineering, University of California, Santa Cruz, Santa Cruz, USA.
Navigating unfamiliar environments can be challenging for visually impaired individuals due to difficulties in recognizing distant landmarks or visual cues. This work focuses on a particular form of wayfinding, specifically backtracking a previously taken path, which can be useful for blind pedestrians. We propose a hands-free indoor navigation solution using a smartphone without relying on pre-existing maps or external infrastructure.
View Article and Find Full Text PDFPhys Imaging Radiat Oncol
January 2025
Aarhus University Hospital, Danish Centre for Particle Therapy, Palle Juul-Jensens Blvd. 25, 8200 Aarhus, Denmark.
Background And Purpose: Diffusion tensor imaging (DTI) has been proposed to guide the anisotropic expansion from gross tumor volume to clinical target volume (CTV), aiming to integrate known tumor spread patterns into the CTV. This study investigate the potential of using a DTI atlas as an alternative to patient-specific DTI for generating anisotropic CTVs.
Materials And Methods: The dataset consisted of twenty-eight newly diagnosed glioblastoma patients from a Danish national DTI protocol with post-operative T1-contrast and DTI imaging.
Lancet Planet Health
January 2025
Washington State University, Pullman, WA, USA.
Background: An increase in pandemics of zoonotic origin has led to a growing interest in using statistical prediction to identify hotspots of zoonotic emergence. However, the rare nature of pathogen emergence requires modellers to impose simplifying assumptions, which limit the model's validity. We present a novel approach to hotspot mapping that aims to improve validity by combining model-based insights with expert knowledge.
View Article and Find Full Text PDFQuant Imaging Med Surg
January 2025
Paul. C. Lauterbur Research Centers for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Background: Brain temperature signifies the thermal homeostasis of the tissue, and may serve as a marker for neuroprotective therapy. Currently, it remains challenging to map the human brain temperature with high spatial resolution. The thermal dependence of chemical exchange saturation transfer (CEST) effects of endogenous labile protons may provide a promising mechanism for the absolute brain temperature imaging.
View Article and Find Full Text PDFSci Rep
January 2025
North University of China, School of Mechanical Engineering, Taiyuan, 030051, Shanxi, China.
To improve the efficiency of mobile robot movement, this paper investigates the fusion of the A* algorithm with the Dynamic Window Approach (DWA) algorithm (IA-DWA) to quickly search for globally optimal collision-free paths and avoid unknown obstacles in time. First, the data from the odometer and the inertial measurement unit (IMU) are fused using the extended Kalman filter (EKF) to reduce the error caused by wheel slippage on the mobile robot's positioning and improve the mobile robot's positioning accuracy. Second, the prediction function, weight coefficients, search neighborhood, and path smoothing processing of the A* algorithm are optimally designed to incorporate the critical point information in the global path into the DWA calculation framework.
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