Ball-path inference based on a combination of audio and video clues in tennis video sequences

Tennis-sports analysis is attracting much attention in content-analysis research and professional applications.This paper presents a scheme for sports analysis employing an automatic tennis ball-path inference driven by a combination of auditory and visual information. The ball-path inference is implemented for tactics analysis.Since ball tracking remains to be a challenging issue in practice, we use a non-tracking approach for ball-path inference. We propose an effective serving-player detection for achieving an accurate match between a sequence of racket-hit moments and the position of the hitting player in the corresponding video frames. Experimental results have shown that the proposed system can reliably detect the serving-player and classify into different categories, such as left-court/right-court service and frontcourt/ back-court service. Therefore, our system can be utilized for an effective and automatic extraction of various tennis events, performance and tactics analysis with high reliability

Fast detection and modeling of human-body parts from monocular video

This paper presents a novel and fast scheme to detect different body parts in human motion. Using monocular video sequences, trajectory estimation and body modeling of moving humans are combined in a co-operating processing architecture. More specifically, for every individual person, features of body ratio, silhouette and appearance are integrated into a hybrid model to detect body parts. The conventional assumption of upright body posture is not required. We also present a new algorithm for accurately finding the center point of the human body. The body configuration is finally described by a skeleton model. The feasibility and accuracy of the proposed scheme are analyzed by evaluating its performance for various sequences with different subjects and motion types (walking, pointing, kicking, leaping and falling). Our detection system achieves nearly real-time performance (around 10 frames/second)

Comparison of chemical profiles and effectiveness between Erxian decoction and mixtures of decoctions of its individual herbs : a novel approach for identification of the standard chemicals

Acknowledgements This study was partially supported by grants from the Seed Funding Programme for Basic Research (Project Number 201211159146 and 201411159213), the University of Hong Kong. We thank Mr Keith Wong and Ms Cindy Lee for their technical assistances.Peer reviewedPublisher PD

Innovative Selective Laser Sintering Rapid Manufacturing using Nanotechnology

The objective of this research is to develop an improved nylon 11 (polyamide 11) polymer with enhanced flame retardancy, thermal, and mechanical properties for selective laser sintering (SLS) rapid manufacturing (RM). A nanophase was introduced into nylon 11 via twin screw extrusion to provide improved material properties of the polymer blends. Atofina (now known as Arkema) RILSAN® nylon 11 injection molding polymer pellets was used with three types of nanoparticles: chemically modified montmorillonite (MMT) organoclays, nanosilica, and carbon nanofibers (CNF) to create nylon 11 nanocomposites. Wide angle X-ray diffraction (WAXD) and transmission electron microscopy (TEM) were used to determine the degree of dispersion. Fifteen nylon 11 nanocomposites and control nylon 11 were fabricated by injection molding. Flammability properties (using a cone calorimeter with a radiant flux of 50 kW/m2 ) and mechanical properties such as tensile strength and modulus, flexural modulus, elongation at break were determined for the nylon 11 nanocomposites and compared with the baseline nylon 11. Based on flammability and mechanical material performance, five polymers including four nylon 11 nanocomposites and a control nylon 11 were cryogenically ground into fine powders for SLS RM. SLS specimens were fabricated for flammability, mechanical, and thermal properties characterization. Nylon 11-CNF nanocomposites exhibited the best overall properties for this study.Mechanical Engineerin