浅谈速写的有关概念及其重要性

结合教学实践经验,重点澄清当代艺术教学中对速写概念的一些模糊理解,探讨它的定义与范畴,简介其在人类艺术文化领域等方面发挥的重要作用。     

Jump Filter: A Dynamic Sketch for Big Data Governance

With the rapid development of information technology, the volume of data maintains exponential growth, and the value of data is hard to mine. This brings significant challenges to the efficient management and control of each link in the data life cycle, such as data collection, cleaning, storage, and sharing. Sketch uses a hash table/matrix/bit vector to track the core characteristics of data, such as frequency, cardinality, and membership. This mechanism makes the sketch itself metadata, which has been widely used in sharing, transmission, update, and other scenarios. The rapid flow characteristic of big data has spawned dynamic sketches. The existing dynamic sketches have the advantage of expanding or shrinking the capacity with the size of the data stream by dynamically maintaining a list of probabilistic data structures in a chain or tree structure. However, there are problems with the excessive space overhead and time overhead increasing with the increase in the dataset cardinality. This paper designs a dynamic sketch for big data governance on the basis of the advanced jump consistent hash. This method can simultaneously achieve the space overhead that grows linearly with the dataset cardinality and the constant time overhead of data processing and analysis, effectively supporting the demanding big data processing and analysis tasks for big data governance. The validity and efficiency of the proposed method are verified by the comparison with traditional methods on various synthetic and natural datasets.     

A global energy optimization framework for 2.1D sketch extraction from monocular images

The 2.1D sketch is a layered image representation, which assigns a partial depth ordering of over-segmented regions in a monocular image. This paper presents a global optimization framework for inferring the 2.1D sketch from a monocular image. Our method only uses over-segmented image regions (i.e., superpixels) as input, without any information of objects in the image, since (1) segmenting objects in images is a difficult problem on its own and (2) the objective of our proposed method is to be generic as an initial module useful for downstream high-level vision tasks. This paper formulates the inference of the 2.1D sketch using a global energy optimization framework. The proposed energy function consists of two components: (1) one is defined based on the local partial ordering relations (i.e., figure-ground) between two adjacent over-segmented regions, which captures the marginal information of the global partial depth ordering and (2) the other is defined based on the same depth layer relations among all the over-segmented regions, which groups regions of the same object to account for the over-segmentation issues. A hybrid evolution algorithm is utilized to minimize the global energy function efficiently. In experiments, we evaluated our method on a test data set containing 100 diverse real images from Berkeley segmentation data set (BSDS500) with the annotated ground truth. Experimental results show that our method can infer the 2.1D sketch with high accuracy.     

基于人脸特征和线积分卷积的肖像素描生成

为了更好地模拟素描的笔画和突显肖像素描中五官的部分,提出基于人脸特征和线积分卷积的肖像素描生成方法.首先进行人脸分割,由人脸特征点确定GrabCut算法中每个特征的初始trimap,然后根据分割结果使用线积分卷积算法绘制肖像素描.文中使用了基于分割结果的多分辨率白噪声和方向场,并提出了基于分割结果的自适应性边界提取算法.实验结果表明,该算法改善了肖像素描的生成效果.     

基础素描课程“启发性教学”的研究

针对素描教学中存在的实际问题,通过素描色调训练、构成组合训练、绘画材料表现等3方面研究教学中的启发性素描的教学训练模式,使学生具备较好的绘画表现能力,提高学生的艺术感受能力．     

一种增加LED照明时序彩色投影系统亮度的方法

基于微型投影显示的色域特性和色彩实现机制,提出了一种提高微型投影系统亮度的方法。在基色子帧中引入其它基色,实现基色坐标的变换,再对微型投影系统亮场白平衡,分析并比较系统在绿色基色校正前后的性能。从理论分析了各色LED的最大工作电流、各基色色坐标和白场色坐标对通过基色校正提高亮度效果的影响。将该方法应用于实验室研发的微型投影系统,在保证系统显示性能的同时,亮度有了25.24%的提升。     

大规模数据流统计中冷热流替换策略优化

对大规模数据流统计的问题进行了研究,针对大流统计的典型结构Elastic Sketch替换策略中存在的问题进行优化,优化策略解决了冷流被误判为热流插入重部的问题.针对重部中保存的不一定是最大流的问题进行优化,提出了基于最大值和组相连的替换策略,保证了存储在重部的一定是最大的流,提高了大流统计的精度,同时大大降低了热碰撞发生的概率.相比于传统的测量统计方法,在提高了测量精度的同时,减少了内存占用.     

基于分类字典的多内容灰度图像彩色化算法

为解决基于字典学习与稀疏表示的灰度图像彩色化算法只对单一内容图像有效这一问题,提出了一种新型的图像彩色化方法. 首先,根据目标灰度图像的子内容分别选取多组参考彩色图像,从各组参考彩色图像中选取对应子内容的样本图像块;然后,分别进行字典训练,得到基于内容的分类字典;最后,根据重建误差最小化原则,查找最佳匹配字典,进而实现灰度图像的彩色化. 该算法是一种自动算法,在保证图像彩色化过程自动化的前提下,提高了彩色化效果. 实验结果表明:该算法能够对目标灰度图像中的不同内容分别进行正确彩色化处理.     

基于虚拟人的汽车内饰造型草图设计方法研究

基于当前汽车内饰造型草图设计中存在的问题,引入虚拟人技术生成造型草图设计的辅助模板,建立了基于辅助模板的造型草图设计新方法,并将设计方法进行设计实践,用实际效果验证理论,从而为汽车内饰设计师提供了一种快捷而有效的技术支持方案。     

面向草图检索的小样本增量有偏学习算法

为了解决草图检索相关反馈中小样本训练、数据不对称及实时性要求这3个难点问题,提出了一种小样本增量有偏学习算法.该算法将主动式学习、有偏分类和增量学习结合起来,对相关反馈过程中的小样本有偏学习问题进行建模.其中,主动式学习通过不确定性采样,选择最佳的用户标注样本,实现有限训练样本条件下分类器泛化能力的最大化;有偏分类通过构造超球面区别对待正例和反例,准确挖掘用户目标类别;每次反馈循环中新加入的样本则用于分类器的增量学习,在减少分类器训练时间的同时积累样本信息,进一步缓解小样本问题.实验结果表明,该算法可以有效地改善草图检索性能,也适用于图像检索和三维模型检索等应用领域.