A new parallel particle filter face tracking method based on heterogeneous system

This paper proposed a multi-cue-based face-tracking algorithm with the supporting framework using parallel multi-core and one Graphic Processing Unit (GPU). Due to illumination and partial-occlusion problems, face tracking usually cannot stably work based on a single cue. Focusing on the above-mentioned problems, we first combined three different visual cues??color histogram, edge orientation histogram, and wavelet feature??under the framework of particle filters to considerably improve tracking performance. Furthermore, an online updating strategy made the algorithm adaptive to illumination changes and slight face rotations. Subsequently, attempting two parallel approaches resulted in real-time responses. However, the computational efficiency decreased considerably with the increase of particles and visual cues. In order to handle the large amount of computation costs resulting from the introduced multi-cue strategy, we explored two parallel computing techniques to speed up the tracking process, especially the most computation-intensive observational steps. One is a multi-core-based parallel algorithm with a MapReduce thread model, and the other is a GPU-based speedup approach. The GPU-based technique uses features-matching and particle weight computations, which have been put into the GPU kernel. The results demonstrate that the proposed face-tracking algorithm can work robustly with cluttered backgrounds and differing illuminations; the multi-core parallel scheme can increase the speed by 2?C6 times compared with that of the corresponding sequential algorithms. Furthermore, a GPU parallel scheme and co-processing scheme can achieve a greater increase in speed (8×?C12×) compared with the corresponding sequential algorithms.     

基于互联网图像集的室外场景建模技术综述

目前在互联网上有海量的室外场景照片,它们不仅内容覆盖面广,对同一场景有大量不同视点和光照条件下的采样,而且获取成本很低.如何利用这些照片中包含的丰富场景信息,快速、方便地构造各种逼真的虚拟场景,是互联网迅猛发展给虚拟现实、计算机图形学和计算机视觉带来的新的研究课题之一.文中分析、总结了近年来国内外互联网图像的真实场景几何建模、自然光照建模和材质反射属性建模的最新研究进展,并对其未来的发展趋势提出了一些看法.     

曲线曲面小波变换的边界连续性保持

现有的小波分解边界连续性保持方法由于将去除的节点全部插回,摒弃了数据压缩特性.为此在曲线小波分解边界处理方面提出2种基于数据压缩的连续性保持方法:一是插入与Cr连续相关的节点,然后调整相应的控制顶点与高分辨曲线的控制顶点保持一致;二是不插入节点,直接调整与Cr连续相关的控制顶点.在曲面方面,提出了曲面分裂法和T曲面法:通过插入重节点把曲面分裂成边界部分和中心部分并对边界部分插入节点,再调整相应的控制顶点与高分辨曲面的重合;构造了T网格,使其边界部分与高分辨曲面一致,中心部分与低分辨曲面一致.最后把T曲面方法推广到周期曲面小波变换边界处理上.实验结果表明,文中方法既保证了小波分解后模型的边界连续,又保留了数据压缩特性.     

Fast calculation of computer generated hologram based on single Fourier transform for holographic three-dimensional display

We present an efficient method for the fast calculation of computer generated hologram (CGH). The 3D object is split into sub-layers according to its depth information. A 2D all-in-focus image is generated by sequential tiling all the layers in one plane. A Fourier hologram that contains all the information of 3D object is calculated from the fast Fourier transform (FFT) of the reassembled 2D image. By multiplying a pre-calculated multifocal off-axis digital phase mask (DPM) to the Fourier hologram, the content of each layer is axially relocated to different depth in the Fourier transform optical system to reconstruct the 3D object. The computation speed of the proposed method is greatly improved with only single FFT calculation process. Both of simulation and experimental results proves the validation of the proposed method.     

Bayesian network based general correspondence retrieval method for depth sensing with single-shot structured light

This study reinvestigated one of the most fundamental problems in structure light depth sensing field: correspondence retrieval of features between patterns and images. We formulate the global optimum correspondence retrieval by maximizing a conditional probability of correspondence given observed features, which is depicted by a Bayesian network. Different from traditional “code-only” based correspondence retrieval methods, the proposed Bayesian network based method exploits the positional correlations of correspondences of neighboring features, namely, the correspondences of poorly detected features are estimated with the aid of the correspondences of well detected features. The method performs especially well on challenging scenes with rich depth variations, abrupt depth changes, edges, etc. Experiments show that the proposed method increase the correspondence accuracy by about 40% on challenging scenes, compared with traditional “code-only” based correspondence retrieval methods.     

An adaptive region segmentation combining surrogate model applied to correlate design variables and performance parameters in a transonic axial compressor

Surrogate models have been widely applied to correlate design variables and performance parameters in turbomachinery optimization applications. With more design variables and uncertain factors taken into account in an optimization design problem, the mathematical relations between the design variables and the performance parameters might present linear, low-order nonlinear or even high-order nonlinear characteristics, and are usually analytically unknown. Therefore, it is required that surrogate models have high adaptability and prediction accuracy for both the linear and nonlinear characteristics. The paper mainly investigates the effectiveness of an adaptive region segmentation combining surrogate model based on support vector regression and kriging model applied to a transonic axial compressor to approximate the complicated relationships between geometrical variables and objective performance outputs with different sampling methods and sizes. The purpose is to explore the prediction accuracy and computational efficiency of this adaptive surrogate model in real turbomachinery applications. Three different sampling techniques are studied: (1) uniform design; (2) Latin hypercube sampling method; (3) Sobol quasi-random design. For the low dimensional case with five variables, the adaptive region segmentation combining surrogate model performs better (not worse) than the single component surrogate in terms of prediction accuracy and computational efficiency. In the meanwhile, it is also noted that the uniform design applied to the adaptive surrogate model has more advantages over the Latin hypercube sampling method especially for the small sample size cases, both performing better than the Sobol quasi-random design. Moreover, a high dimensional case with 12 variables is also utilized to further validate the prediction advantage of the adaptive region segmentation combining surrogate model over the single component surrogate, and the computational results favor it. Overall, the adaptive region segmentation combining surrogate model has produced acceptable to high prediction accuracy in presenting complex relationships between the geometrical variables and the objective performance outputs and performed robustly for a transonic axial compressor problem.

     

Comparison of three internationally certified firefighter protective ensembles: Physiological responses,mobility, and comfort

BackgroundFire protective ensembles (FPEs) are essential to safely perform firefighting job tasks; however, they are often burdensome to the workers. The aim of this study was to compare three internationally certified fire protective ensembles from the European Union (EU), South Korea (SK), and United States (US) on physiological responses, mobility, and comfort.MethodsTen male professional firefighters performed a battery of exercises in the laboratory following the ASTM F3031-17 standard to evaluate mobility, occupation-specific performance, and physiological responses (body weight, heart rate (HR), core temperature (T_c), breathing rate (BR), and rating of perceived exertion (RPE)) to 20 min of treadmill walking (3.2 mph, 5% incline). All participants carried out the evaluation wearing each FPE in a random order. Mixed effects models examined time (pre-vs. post-) by ensemble (EU, SK, US) interactions for all physiological variables and compared comfort, performance, and subjective variables across ensembles.ResultsNo interaction effects were observed for body weight, HR, T_c, BR, or RPE (p = 0.890, p = 0.994, p = 0.897, p = 0.435, and p = 0.221; respectively). SK had greater trunk flexion than EU (78.4° vs. 74.6°, p = 0.026) and US had lower standing reach than EU (105.5 cm vs. 115.4 cm, p = 0.004). Agility circuit time was lower in US (9.3 s) compared to EU (9.8 s) or SK (9.9 s) (p = 0.051 and p = 0.019, respectively).ConclusionsThe findings suggest that physiological burden remained largely unchanged across the international FPEs. However, mobility, performance, and comfort may be significantly influenced across types. International stakeholders and end users should consider design implications when choosing fire protective ensembles.     

Image quality evaluation for OLED-based smart-phone displays at various lighting conditions

The image quality of three organic light-emitting diode (OLED) based smart-phone displays was assessed at three levels of ambient lighting conditions corresponding to the darkroom, indoor and outdoor environment, respectively. Seven perceptual attributes, i.e., naturalness, colorfulness, brightness, contrast, sharpness, preference, and overall image quality (IQ), were evaluated in both standard dynamic range (SDR) and high dynamic range (HDR) mode via psychophysical experiments by rank order method, while readability was assessed only in SDR mode and gradation was investigated only in HDR mode. The experimental results demonstrate that, besides the color gamut, the tone reproduction curve is also an important factor affecting the colorfulness of mobile display in the two modes. Higher peak luminance would not mean better performance on brightness and contrast for HDR images, which is opposite to SDR mode. Further analysis of variance (ANOVA) indicates that the ranking results of all perceptual attributes are not significantly affected by the ambient lighting levels in both SDR and HDR modes.     

Investigation of oil palm harvesting tools design and technique on work-related musculoskeletal disorders of the upper body

The oil palm industry is one of the important sectors in Malaysia. The growth and development of this industry shows that Malaysia is the world second-largest oil palm producers. However, in the fresh fruit bunch (FFB) harvesting process, the harvesters are exposed to many types of work-related musculoskeletal disorders (WMSDs). The FFB harvesters tend to develop WMSDs especially the shoulders and trunk. Hence, it is important to identify the exposure levels, awkward postures and the reaction forces of muscle activity based on the posture and movement of the harvesters when using pole, chisel and loading spike during the harvesting process. The objective of this study was to investigate the effect of the design of oil palm FFB harvesting tools on WMSDs of the upper body. Rapid Upper Limb Analysis (RULA) was used to investigate and assess the exposure level on the harvester body during the harvesting process. The assessment showed that the shoulders and trunk have high exposure level and undergo awkward posture. Human Musculoskeletal Model Analysis (HMMA) was used to identify the reaction force exerted on the muscle during the FFB harvesting process. In this study, 4 muscles were analysed including Triceps, Biceps, Erector Spinae and Psoas Major. The highest reaction force of 16.36 N was found on the left triceps when handling a loading spike. In conclusion, it is important to address the risks by reviewing all possible aspects that contribute to the WMSDs and interventions on the tool design, task and working shifts may be required.     

The ability of eye-tracking metrics to classify and predict the perceived driving workload

Traffic safety is directly related to the mental and physical condition of the driver. Performing regular secondary tasks while driving is an additional activity that dissipates attention and adds to the drivers' workload. Identifying driver fatigue and workload based on gaze behavior is one way to ensure a safe driving experience. The purpose of this paper is to classify and predict driving perceived workload using a set of eye-tracking metrics (gaze fixation, duration, pointing, and pupil diameter). The ability of eye-tracking metrics to predict driving workload has been investigated. As a result, frustration, performance, and temporal load showed a correlation with gaze metrics. Gaze point, duration, fixation, and pupil diameter significantly influence driving workload.Relevance to industry: Results will supply the specialists in eye-tracking/sensor technologies and traffic safety with new knowledge to improve the design of the driving performance and safety monitoring systems and efficiency of the driving process.