Perceptually Motivated BRDF Comparison using Single Image

Surface reflectance of real‐world materials is now widely represented by the bidirectional reflectance distribution function (BRDF) and also by spatially varying representations such as SVBRDF and the bidirectional texture function (BTF). The raw surface reflectance measurements are typically compressed or fitted by analytical models, that always introduce a certain loss of accuracy. For its evaluation we need a distance function between a reference surface reflectance and its approximate version. Although some of the past techniques tried to reflect the perceptual sensitivity of human vision, they have neither optimized illumination and viewing conditions nor surface shape. In this paper, we suggest a new image‐based methodology for comparing different anisotropic BRDFs. We use optimization techniques to generate a novel surface which has extensive coverage of incoming and outgoing light directions, while preserving its features and frequencies that are important for material appearance judgments. A single rendered image of such a surface along with simultaneously optimized lighting and viewing directions leads to the computation of a meaningful BRDF difference, by means of standard image difference predictors. A psychophysical experiments revealed that our surface provides richer information on material properties than the standard surfaces often used in computer graphics, e.g., sphere or blob.     

Determination of optimal product styles by ordinal logistic regression versus conjoint analysis for kitchen faucets

In this study, a two-stage integrated approach is proposed and implemented to explore user perceptions about kitchen faucet styles and to find optimal levels of design parameters related to product appearance. At the first stage, a group of representative users have been asked to judge 38 systematically selected different faucet designs by using a semantic differential (SD) scale for 11 image (kansei) words about their visual perceptions. Then the relations between overall preference and kansei word scores of users are investigated by Ordinal Logistic Regression (OLOGREG). The model obtained helps understand how customers describe highly preferred designs. It can also be used to confirm if a product design will be highly preferred. At the second stage, the relations between overall preference scores and design parameter levels related to the product appearance are modeled using again OLOGREG, and then the best design parameter levels for visual perceptions are found by maximizing the overall preference scores. The results are confirmed and discussed. They are also compared to those of a commonly used approach in the literature, Conjoint Analysis (CA). This comparison has showed that the OLOGREG approach is superior to traditional CA. Finally, it is discussed how the product style design optimization approach presented and demonstrated in this study for the case of some kitchen faucets can be used in general for other products.Relevance to industry: Developing a user-centered product is an important policy of an enterprise in today's highly competitive marketplace. To reach this objective, a systematic method is proposed by integrating several techniques. This method will be useful to any industry that designs and produces consumer products. These products more fit the consumer needs and the competitiveness of them are improved.     

Affective evaluation of user impressions using virtual product prototyping

This study aims to develop an effective and efficient method of analyzing user impressions of a product using virtual prototyping. A method to analyze the relationship between user impressions and design elements of a product using virtual prototyping was proposed, and then the method was applied to the case study of automobile interior design. Thirty‐two participants in the experiment evaluated 32 different virtual prototypes of automobile interiors generated from the combination of 17 design elements. The results of the case study showed that user impressions can be well explained by design elements. Physically large design elements, such as the shapes of frontal area, center fascia, door trim, and steering wheel, were critical areas of automobile interior design. The proposed method is expected to be an effective and efficient alternative for industrial practitioners to analyze user impressions of design alternatives at the early stage of the design process. © 2010 Wiley Periodicals, Inc.     

基于主客观综合权重的云服务时间序列选择算法

目前已有的云服务时间序列选择算法没有很好地考虑用户的QoS（quality of service）偏好信息,而传统的用户偏好算法只适用于QoS指标值为单一数值的情况,在QoS指标值为时间序列向量的情况下无法进行有效计算.因此,本文提出了一种基于主客观综合权重的云服务时间序列选择算法（Time series of cloud services selection algorithm employing subjective and objective weight,简称TCSOW）.此算法从基于用户QoS偏好层次的主观权重计算方法和基于QoS指标相关性的客观权重计算方法这两个角度进行详细描述,通过结合时间序列QoS模型进行云服务选择.实验分析表明,提出的TCSOW算法在有效解决用户QoS偏好的同时又充分考虑云服务集的QoS指标数据分布特性,使最终的度量结果具有较高的准确性与科学性.     

基于LBSN好友关系的个性化景点推荐方法

基于位置的社交网络（LBSN）中照片带有丰富时间空间位置信息,为发掘用户偏好信息、进行景点推荐提供了条件。现有推荐方法存在推荐条件单一、难以准确估算用户偏好、推荐结果准确性不高的问题。改进传统协同过滤中相似用户计算和推荐方法,提出PTLR方法。通过用户景点照片矩阵计算用户偏好,结合好友亲密度信任关系计算相似邻居。利用多条件如兴趣偏好、景点时间适宜程度及候选周边关联景点产生推荐。实验结果表明PTLR能有效提高推荐准确性。     

Enhanced 3D shape recovery using the neural-based hybrid reflectance model.

It is known that most real surfaces usually are neither perfectly Lambertian model nor ideally specular model; rather, they are formed by the hybrid structure of these two models. This hybrid reflectance model still suffers from the noise, strong specular, and unknown reflectivity conditions. In this article, these limitations are addressed, and a new neural-based hybrid reflectance model is proposed. The goal of this method is to optimize a proper reflectance model by learning the weight and parameters of the hybrid structure of feedforward neural networks and radial basis function networks and to recover the 3D object shape by the shape from shading technique with this resulting model. Experimental results, including synthetic and real images, were performed to demonstrate the performance of the proposed reflectance model in the case of different specular effects and noise environments.     

基于联合分析法的智能手环用户偏好量化模型构建

通过对智能手环的造型、功能及交互方式进行实证量化研究,探究智能手环设计 要素对用户偏好的量化影响。采用联合分析法,首先通过评价构造法解析出影响用户偏好的智 能手环设计要素,然后通过主成分分析法筛选关键设计要素,并通过相关文献及智能手环竞品 分析确定各关键设计要素的水平。最后将智能手环关键设计要素及水平进行组合形成虚拟手环 产品样本,通过联合分析法构建智能手环设计要素的用户偏好联合分析模型。确定了用户偏好 联合分析模型10 个关键设计要素与27 个水平及权重,并在此基础上提出智能手环设计策略, 为智能手环设计提供理论参考。     

Real‐time Image‐based Lighting of Microfacet BRDFs with Varying Iridescence

Iridescence is a natural phenomenon that is perceived as gradual color changes, depending on the view and illumination direction. Prominent examples are the colors seen in oil films and soap bubbles. Unfortunately, iridescent effects are particularly difficult to recreate in real‐time computer graphics. We present a high‐quality real‐time method for rendering iridescent effects under image‐based lighting. Previous methods model dielectric thin‐films of varying thickness on top of an arbitrary micro‐facet model with a conducting or dielectric base material, and evaluate the resulting reflectance term, responsible for the iridescent effects, only for a single direction when using real‐time image‐based lighting. This leads to bright halos at grazing angles and over‐saturated colors on rough surfaces, which causes an unnatural appearance that is not observed in ground truth data. We address this problem by taking the distribution of light directions, given by the environment map and surface roughness, into account when evaluating the reflectance term. In particular, our approach prefilters the first and second moments of the light direction, which are used to evaluate a filtered version of the reflectance term. We show that the visual quality of our approach is superior to the ones previously achieved, while having only a small negative impact on performance.     

Affective preference measurement of product appearance based on event-related potentials

The product appearance plays an important role in users’ purchase decision, while the emotions elicited by the product appearance are subtle, low intensity and not easy to obtain. Event-related potentials (ERPs) can reflect people’s psychological activities and effectively identify the characteristics of brain’s affective process. In the present study, the affective preference measurement of humidifier appearance was conducted based on the theory of affective design and event-related potentials. Firstly, the collected humidifier pictures were screened to be the experimental stimuli through multidimensional scaling analysis and cluster analysis. During the affective preference measurement experiment, the participants were asked to judge the affective preference level (liked vs. neutral vs. disliked) of humidifier pictures with the mouse button clicking (left, middle, right), and the electroencephalograph signals were recorded at the same time. ERPs results showed that the frontal and central N1 and frontal, frontal–central and central late positive potential can be taken as the indexes to measure participants’ affective preference of humidifier appearance. In conclusion, the participants’ affective preference level of humidifier appearance can be measured by ERPs. The experiment results can be used to guide product design, by measuring the brain activities of different prototypes at the phase of product development we can roughly infer which one is the user preferred or not preferred.