Temporal Variations in Visual Completion: A Reflection of Spatial Limits?

The completion of partly occluded objects appears instantaneous and effortless, but empirically takes measurable time. The current study investigates how amount of occlusion affects the time course and mechanisms of visual completion. Experiment 1 used a primed-matching paradigm to determine completion times for objects occluded by various amounts. Experiments 2 and 3 used a dot-localization paradigm to probe completed contour representations for a qualitative shift above some spatial limit. The results demonstrate that time to completion rises with amount of occlusion. Nonetheless, the visual system can complete highly occluded objects, even when the occlusion renders visible contours nonrelatable. Furthermore, prolonged completion times for highly occluded objects do not result from a breakdown of low-level interpolation processes: The same contour completion mechanism operates on objects occluded by different spatial extents. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

烟气污染物协同治理中的负协同效应串联作用现象

随着烟气污染物协同治理技术在燃煤电站的普遍应用,协同治理过程中各单元设备间的不良影响及其造成的设备治理能力下降或污染物增量排放现象日益显现,对此类负协同效应展开分析,并通过性能试验、检测化验、运行诊断等方法对某350 MW机组进行研究,结果表明：存在负协同效应串联作用现象,即上游设备的负协同效应不断蚕食本体或下游设备的污染物治理能力,最终导致设备治理能力不足。最后,提出控制及消纳负协同效应的建议。     

铝合金彩色瓷质阳极氧化新工艺

研究了在铝合金瓷质阳极氧化膜层表面进行染色、封闭一步处理的新工艺.通过对这种方法得到的瓷质阳极氧化膜层进行耐磨、耐腐蚀、耐候等性能试验,发现经过瓷质氧化后表面,进行染色封闭一步处理的膜层具有色泽正、染色牢固、表面装饰效果好的特点;同时这种瓷质彩色膜层还具有良好的耐磨、耐腐蚀和耐候性能.     

基于统计模型的三维场景重建补洞算法

提出了一种新的处理距离图像(即点云数据)算法。算法提取已经获得的表面数据的特性．计算各个被测的特征值,建立马尔可夫统计模型,描述整个表面的数学特征,进而利用最大似然概率预测丢失位置的数据值,得到被测物体表面的完整的数据描述。使用该算法恢复由于障碍物和表面小良反射特性产生的空洞,具有良好的视觉效果．与测量获得的表面数据具有统一的几何特征。     

一种改进型的粒子滤波器

针对复杂背景条件下图像序列中跟踪运动目标的问题,提出一种改进的粒子滤波图像跟踪算法,该算法利用遗传算法的研究成果,采用选择、交叉、变异等步骤实现对粒子的重采样,解决了粒子滤波器所面临的粒子退化和匮乏问题.由于该算法利用了遗传算法的全局寻优特性,因此该算法具有较强的稳健性.同时,粒子滤波可实现非线性非高斯状态空间模型的最优估计,将该粒子滤波用于目标跟踪,具有较好的过遮挡能力.实验结果表明,该算法状态估计性能好,能够很好地实现复杂图像序列中的目标跟踪.     

基于结构化遮挡编码和极限学习机的局部遮挡人脸识别

提出使用结构化遮挡编码（SOC）结合极限学习机（ELM）的算法来处理人脸识别中的遮挡问题。首先，使用SOC去除图像上的遮挡物，将遮挡物体与人脸分离开；同时，通过局部性约束字典（LCD）来估计遮挡物的位置，建立遮挡字典和人脸字典。然后，将建立好的人脸字典矩阵进行归一化处理，并利用ELM对归一化的数据进行分类识别。最后，在AR人脸库上进行的仿真实验结果表明，所提方法对不同遮挡物和不同区域遮挡的图像具有较好的识别率和鲁棒性。     

Topical delivery of tetrahydrocurcumin lipid nanoparticles effectively inhibits skin inflammation: in vitro and in vivo study

Tetrahydrocurcumin (THC) also referred to as ‘white curcumin’, is a stable colorless hydrogenated product of curcumin with superior antioxidant and anti-inflammatory properties. The present study is an attempt to elevate the topical bioavailability of THC, post-incorporation into a nano-carrier system with its final dosage as a hydrogel. Lipid nanoparticles of THC (THC-SLNs) prepared by microemulsification technique were ellipsoidal in shape (revealed in transmission electron microscopy) with a mean particle size of 96.6?nm and zeta potential of ?22?mV. Total drug content and entrapment efficiency of THC-SLNs was 94.51%?±?2.15% and 69.56%?±?1.35%, respectively. Differential scanning calorimetry and X-ray diffraction studies confirmed the formation of THC-SLNs. In vitro drug release studies showed the drug release from THC-SLNs gel to follow Higuchi’s equation revealing a Fickian diffusion. Ex vivo permeation studies indicated a 17 times (approximately) higher skin permeation of THC-SLNs gel as compared with the free THC gel. Skin irritation, occlusion, and stability studies indicated the formulation to be nonirritating, and stable with a desired occlusivity. Pharmacodynamic evaluation in an excision wound mice model clearly revealed the enhanced anti-inflammatory activity of THC-SLNs gel and was further confirmed using biochemical and histopathological studies. It is noteworthy to report here that THC-SLNs gel showed significantly better (p?≤?0.001) activity than free THC in gel. As inflammation is innate to all the skin disorders, the developed product opens up new therapeutic avenues for several skin diseases. To the best of our knowledge, this is the first paper elaborating the therapeutic usefulness of white curcumin-loaded lipidic nanoparticles for skin inflammation.     

Emotion Recognition from Occluded Facial Images Using Deep EnsembleModel

Facial expression recognition has been a hot topic for decades, but high intraclass variation makes it challenging. To overcome intraclass variation for visual recognition, we introduce a novel fusion methodology, in which the proposed model first extract features followed by feature fusion. Specifically, RestNet-50, VGG-19, and Inception-V3 is used to ensure feature learning followed by feature fusion. Finally, the three feature extraction models are utilized using Ensemble Learning techniques for final expression classification. The representation learnt by the proposed methodology is robust to occlusions and pose variations and offers promising accuracy. To evaluate the efficiency of the proposed model, we use two wild benchmark datasets Real-world Affective Faces Database (RAF-DB) and AffectNet for facial expression recognition. The proposed model classifies the emotions into seven different categories namely: happiness, anger, fear, disgust, sadness, surprise, and neutral. Furthermore, the performance of the proposed model is also compared with other algorithms focusing on the analysis of computational cost, convergence and accuracy based on a standard problem specific to classification applications.     

基于多模态数据的目标跟踪算法

为解决目标跟踪中目标遮挡、背景复杂等问题,提出一种基于多模态数据的目标跟踪算法。首先对各个模态数据进行像素级融合,以减少单模态数据中信息不足对跟踪结果的影响。然后对融合后的图像提取不同的特征进行滤波,接着将滤波得到的响应图进行决策级融合,以解决因单个模型漂移导致的模型跟踪失败问题。最后根据融合后的响应图的峰值得到跟踪结果。此外,在跟踪过程中加入遮挡检测模块,进一步增强模型鲁棒性。在普林斯顿跟踪基准上对算法进行评估,结果表明,与其他主流算法相比,基于多模态数据的目标跟踪算法在目标遮挡类视频上跟踪精度提升了8.4%,重合成功率提升了3.3%,具有较好的抗遮挡效果。     

基于轮廓分段特征描述的遮挡目标识别算法

针对传统目标识别算法对于遮挡目标识别准确率低的问题,提出了一种基于轮廓分段特征描述的遮挡目标识别算法。该算法首先采用离散曲线演化算法初步划分目标轮廓,根据分段起伏度进行分段优化,得到完整描述目标轮廓特征的有效分段;然后通过动态规划算法分析轮廓分段之间高度函数特征的相似度,利用特征显著度评价分段特征相对于目标整体特征的重要性;最后将分段之间的相似度和其特征显著度相结合,得到衡量识别准确率的联合相似度,获得最终的识别结果。通过对MPEG-7测试集进行实验分析,证明所提算法能够有效地对遮挡目标进行匹配识别,识别率优于常见的遮挡目标识别算法。