Fast human behavior analysis for scene understanding

Human behavior analysis has become an active topic of great interest and relevance for a number of applications and areas of research. The research in recent years has been considerably driven by the growing level of criminal behavior in large urban areas and increase of terroristic actions. Also, accurate behavior studies have been applied to sports analysis systems and are emerging in healthcare. When compared to conventional action recognition used in security applications, human behavior analysis techniques designed for embedded applications should satisfy the following technical requirements: (1) Behavior analysis should provide scalable and robust results; (2) High-processing efficiency to achieve (near) real-time operation with low-cost hardware; (3) Extensibility for multiple-camera setup including 3-D modeling to facilitate human behavior understanding and description in various events. The key to our problem statement is that we intend to improve behavior analysis performance while preserving the efficiency of the designed techniques, to allow implementation in embedded environments. More specifically, we look into (1) fast multi-level algorithms incorporating specific domain knowledge, and (2) 3-D configuration techniques for overall enhanced performance. If possible, we explore the performance of the current behavior-analysis techniques for improving accuracy and scalability. To fulfill the above technical requirements and tackle the research problems, we propose a flexible behavior-analysis framework consisting of three processing-layers: (1) pixel-based processing (background modeling with pixel labeling), (2) object-based modeling (human detection, tracking and posture analysis), and (3) event-based analysis (semantic event understanding). In Chapter 3, we specifically contribute to the analysis of individual human behavior. A novel body representation is proposed for posture classification based on a silhouette feature. Only pure binary-shape information is used for posture classification without texture/color or any explicit body models. To this end, we have studied an efficient HV-PCA shape-based descriptor with temporal modeling, which achieves a posture-recognition accuracy rate of about 86% and outperforms other existing proposals. As our human motion scheme is efficient and achieves a fast performance (6-8 frames/second), it enables a fast surveillance system or further analysis of human behavior. In addition, a body-part detection approach is presented. The color and body ratio are combined to provide clues for human body detection and classification. The conventional assumption of up-right body posture is not required. Afterwards, we design and construct a specific framework for fast algorithms and apply them in two applications: tennis sports analysis and surveillance. Chapter 4 deals with tennis sports analysis and presents an automatic real-time system for multi-level analysis of tennis video sequences. First, we employ a 3-D camera model to bridge the pixel-level, object-level and scene-level of tennis sports analysis. Second, a weighted linear model combining the visual cues in the real-world domain is proposed to identify various events. The experimentally found event extraction rate of the system is about 90%. Also, audio signals are combined to enhance the scene analysis performance. The complete proposed application is efficient enough to obtain a real-time or near real-time performance (2-3 frames/second for 720×576 resolution, and 5-7 frames/second for 320×240 resolution, with a P-IV PC running at 3GHz). Chapter 5 addresses surveillance and presents a full real-time behavior-analysis framework, featuring layers at pixel, object, event and visualization level. More specifically, this framework captures the human motion, classifies its posture, infers the semantic event exploiting interaction modeling, and performs the 3-D scene reconstruction. We have introduced our system design based on a specific software architecture, by employing the well-known "4+1" view model. In addition, human behavior analysis algorithms are directly designed for real-time operation and embedded in an experimental runtime AV content-analysis architecture. This executable system is designed to be generic for multiple streaming applications with component-based architectures. To evaluate the performance, we have applied this networked system in a single-camera setup. The experimental platform operates with two Pentium Quadcore engines (2.33 GHz) and 4-GB memory. Performance evaluations have shown that this networked framework is efficient and achieves a fast performance (13-15 frames/second) for monocular video sequences. Moreover, a dual-camera setup is tested within the behavior-analysis framework. After automatic camera calibration is conducted, the 3-D reconstruction and communication among different cameras are achieved. The extra view in the multi-camera setup improves the human tracking and event detection in case of occlusion. This extension of multiple-view fusion improves the event-based semantic analysis by 8.3-16.7% in accuracy rate. The detailed studies of two experimental intelligent applications, i.e., tennis sports analysis and surveillance, have proven their value in several extensive tests in the framework of the European Candela and Cantata ITEA research programs, where our proposed system has demonstrated competitive performance with respect to accuracy and efficiency

SLS Processing Studies of Nylon 11 Nanocomposites

Selective Laser Sintering (SLS) is widely used for rapid prototyping/manufacturing of nylon 11 and nylon 12 parts. This processing technique has not been explored for nylon nanocomposites. This study investigates the technicalities of processing nylon 11-clay and nylon-carbon nanofiber nanocomposites with SLS. Microstructural analyses of the SLS powders and parts were conducted under SEM. Results suggest that SLS processing is possible with the new nylon 11 nanocomposites. Yet the SLS parts built have inferior properties relative to those of injection molding, suggesting that more fine tuning for the processing is required.Mechanical Engineerin

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)

Parsec-scale jet properties of the gamma-ray quasar 3C 286

The quasar 3C~286 is one of two compact steep spectrum sources detected by the {\it Fermi}/LAT. Here, we investigate the radio properties of the parsec(pc)-scale jet and its (possible) association with the $\gamma$-ray emission in 3C~286. The Very Long Baseline Interferometry (VLBI) images at various frequencies reveal a one-sided core--jet structure extending to the southwest at a projected distance of $\sim$1 kpc. The component at the jet base showing an inverted spectrum is identified as the core, with a mean brightness temperature of $2.8\times 10^{9}$~K. The jet bends at about 600 pc (in projection) away from the core, from a position angle of $-135^\circ$ to $-115^\circ$. Based on the available VLBI data, we inferred the proper motion speed of the inner jet as $0.013 \pm 0.011$ mas yr$^{-1}$ ($\beta_{\rm app} = 0.6 \pm 0.5$), corresponding to a jet speed of about $0.5\,c$ at an inclination angle of $48^\circ$ between the jet and the line of sight of the observer. The brightness temperature, jet speed and Lorentz factor are much lower than those of $\gamma$-ray-emitting blazars, implying that the pc-scale jet in 3C~286 is mildly relativistic. Unlike blazars in which $\gamma$-ray emission is in general thought to originate from the beamed innermost jet, the location and mechanism of $\gamma$-ray emission in 3C~286 may be different as indicated by the current radio data. Multi-band spectrum fitting may offer a complementary diagnostic clue of the $\gamma$-ray production mechanism in this source.Comment: 9 pages, 4 figures, accept for publication in MNRA

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

Character and interface shear strength of accreted ice on subcooled surfaces submerged in fuel

Sudden release of accreted ice in fuel systems could pose a serious challenge in aircraft operation. The resultant snowshower may reach the filter and fuel-oil heat exchanger, causing a restriction in fuel flow to the engine. It is fundamental to have an appreciation of the character and the interface shear strength of the accreted ice in aircraft fuel systems. This helps to recognise factors for the sudden release of the accreted ice and the intensity of the consequential snowshower. An experimental study was carried out to quantify the character and the interface shear strength of accreted ice on subcooled surfaces submerged in jet fuel. Ice was accreted on naked aluminium, painted aluminium and carbon fibre composite surfaces at various subcooled temperatures. The accreted ice was akin to fresh snow and exhibited soft and fluffy attributes. The character may be expressed quantitatively in terms of the porosity and was found to be c. 0·95. The ice weakly adhered to the substrate surfaces, and the interface shear strength was found to be c. 0·36Pa and c. 2·19Pa at the top surface and at the vertical surface of a specimen block, respectively. It was not possible to detect any variation in the porosity and the interface shear strength for different types of surface finishes and differences in water affnity in fuels due to the crude approach in the estimation of these parameters