This paper presents a method leveraging coded motion information to obtain a fast, high quality motion field estimation. The method is inspired by a recent trend followed by a number of top-performing optical flow estimation schemes that first estimate a sparse set of features between two frames, and then use an edge-preserving interpolation scheme (EPIC) to obtain a piecewise-smooth motion field that respects moving object boundaries. In order to skip the time-consuming estimation of features, we propose to directly derive motion seeds from decoded HEVC block motion; we call the resulting scheme "HEVCEPIC". We propose motion seed weighting strategies that account for the fact that some motion seeds are less reliable than others. Experiments on a large variety of challenging sequences and various bit-rates show that HEVC-EPIC runs significantly faster than EPIC flow, while producing motion fields that have a slightly lower average endpoint error (A-EPE). HEVC-EPIC opens the door of seamlessly integrating HEVC motion into video analysis and enhancement tasks. When employed as input to a framerate upsampling scheme, the average Y-PSNR of the interpolated frames using HEVC-EPIC motion slightly outperforms EPIC flow across the tested bit-rates, while running an order of magnitude faster.
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http://dx.doi.org/10.1109/TIP.2018.2813090 | DOI Listing |
Ergonomics
January 2025
School of Kinesiology and Health Studies, Queen's University, Kingston, Ontario, Canada.
Age is associated with increased tissue stiffness and a higher risk of low back pain, particularly in older, sedentary workers who spend long periods sitting. This study explored how trunk stiffness changes with age and its relationship with posture during prolonged sitting in a sample of 37 women aged 20-65 years. Age was assessed as both Chronological Age and Fitness Age, with trunk stiffness measured using a passive trunk flexion apparatus.
View Article and Find Full Text PDFJ Nanobiotechnology
January 2025
School of Medical Imaging, Xuzhou Medical University, Xuzhou, 221004, China.
With the progress of atherosclerosis (AS), the arterial lumen stenosis and compact plaque structure, the thickening intima and the narrow gaps between endothelial cells significantly limit the penetration efficiency of nanoprobe to plaque, weakening the imaging sensitivity and therapy efficiency. Thus, in this study, a HO-NIR dual-mode nanomotor, Gd-doped mesoporous carbon nanoparticles/Pt with rapamycin (RAPA) loading and AntiCD36 modification (Gd-MCNs/Pt-RAPA-AC) was constructed. The asymmetric deposition of Pt on Gd-MCNs catalyzed HO at the inflammatory site to produce O, which could promote the self-motion of the nanomotor and ease inflammation microenvironment of AS plaque.
View Article and Find Full Text PDFInsights Imaging
January 2025
IRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
Entrapment neuropathies at the elbow are common in clinical practice and require an accurate diagnosis for effective management. Understanding the imaging characteristics of these conditions is essential for confirming diagnoses and identifying underlying causes. Ultrasound serves as the primary imaging modality for evaluating nerve structure and movement, while MRI is superior for detecting muscle denervation.
View Article and Find Full Text PDFEur Radiol
January 2025
Departments of Radiology and Nuclear Medicine, Erasmus MC - Sophia Children's Hospital, Rotterdam, the Netherlands.
Chest imaging in children presents unique challenges due to varying requirements across age groups. For chest radiographs, achieving optimal images often involves careful positioning and immobilisation techniques. Antero-posterior projections are easier to obtain in younger children, while lateral decubitus radiographs are sometimes used when expiratory images are difficult to obtain and for free air exclusion.
View Article and Find Full Text PDFSci Rep
January 2025
School of Fashion and Textiles, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
This study presents an advanced dynamic finite element (FE) model of multiple components of the breast to examine the biomechanical impact of different types of physical activities and activity intensity on the breast tissues. Using 4D scanning and motion capture technologies, dynamic data are collected during different activities. The accuracy of the FE model is verified based on relative mean absolute error (RMAE), and optimal material parameters are identified by using a validated stepwise grid search method.
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