A Mobile Landmarks Guide : Outdoor Augmented Reality based on LOD and Contextual Device (모바일 랜드마크 가이드 : LOD와 문맥적 장치 기반의 실외 증강현실)
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- Journal of Intelligence and Information Systems
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- v.18 no.1
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- pp.1-21
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- 2012
In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.
With the development of the web, two-way communication and evaluation became possible and marketing paradigms shifted. In order to meet the needs of consumers, web design trends are continuously responding to consumer feedback. As the web becomes more and more important, both academics and businesses are studying consumer emotions and satisfaction on the web. However, some consumer characteristics are not well considered. Demographic characteristics such as age and sex have been studied extensively, but few studies consider psychological characteristics such as regulatory focus (i.e., emotional regulation). In this study, we analyze the effect of web style on consumer emotion. Many studies analyze the relationship between the web and regulatory focus, but most concentrate on the purpose of web use, particularly motivation and information search, rather than on web style and design. The web communicates with users through visual elements. Because the human brain is influenced by all five senses, both design factors and emotional responses are important in the web environment. Therefore, in this study, we examine the relationship between consumer emotion and satisfaction and web style and design. Previous studies have considered the effects of web layout, structure, and color on emotions. In this study, however, we excluded these web components, in contrast to earlier studies, and analyzed the relationship between consumer satisfaction and emotional indexes of web-style only. To perform this analysis, we collected consumer surveys presenting 40 web style themes to 204 consumers. Each consumer evaluated four themes. The emotional adjectives evaluated by consumers were composed of 18 contrast pairs, and the upper emotional indexes were extracted through factor analysis. The emotional indexes were 'softness,' 'modernity,' 'clearness,' and 'jam.' Hypotheses were established based on the assumption that emotional indexes have different effects on consumer satisfaction. After the analysis, hypotheses 1, 2, and 3 were accepted and hypothesis 4 was rejected. While hypothesis 4 was rejected, its effect on consumer satisfaction was negative, not positive. This means that emotional indexes such as 'softness,' 'modernity,' and 'clearness' have a positive effect on consumer satisfaction. In other words, consumers prefer emotions that are soft, emotional, natural, rounded, dynamic, modern, elaborate, unique, bright, pure, and clear. 'Jam' has a negative effect on consumer satisfaction. It means, consumer prefer the emotion which is empty, plain, and simple. Regulatory focus shows differences in motivation and propensity in various domains. It is important to consider organizational behavior and decision making according to the regulatory focus tendency, and it affects not only political, cultural, ethical judgments and behavior but also broad psychological problems. Regulatory focus also differs from emotional response. Promotion focus responds more strongly to positive emotional responses. On the other hand, prevention focus has a strong response to negative emotions. Web style is a type of service, and consumer satisfaction is affected not only by cognitive evaluation but also by emotion. This emotional response depends on whether the consumer will benefit or harm himself. Therefore, it is necessary to confirm the difference of the consumer's emotional response according to the regulatory focus which is one of the characteristics and viewpoint of the consumers about the web style. After MMR analysis result, hypothesis 5.3 was accepted, and hypothesis 5.4 was rejected. But hypothesis 5.4 supported in the opposite direction to the hypothesis. After validation, we confirmed the mechanism of emotional response according to the tendency of regulatory focus. Using the results, we developed the structure of web-style recommendation system and recommend methods through regulatory focus. We classified the regulatory focus group in to three categories that promotion, grey, prevention. Then, we suggest web-style recommend method along the group. If we further develop this study, we expect that the existing regulatory focus theory can be extended not only to the motivational part but also to the emotional behavioral response according to the regulatory focus tendency. Moreover, we believe that it is possible to recommend web-style according to regulatory focus and emotional desire which consumers most prefer.
Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking (
This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.
The study examines how the environmental factors of store influence service brand personality and repurchase intention in the service environment. The service industry has been experiencing the intensified competition with the industry's continuous growth and the influence from rapid technological advancement. Under the circumstances, it has become ever more important for the brand competitiveness to be distinctively recognized against competition. A brand needs to be distinguished and differentiated from competing companies because they are all engaged in the similar environment of the service industry. The differentiation of brand achievement has become increasingly important to highlight certain brand functions to include emotional, self-expressive, and symbolic functions since the importance of such functions has been further emphasized in promoting consumption activities. That is the recent role of brand personality that has been emphasized in the service industry. In other words, customers now freely and actively express their personalities or egos in consumption activities, taking an important role in construction of a brand asset. Hence, the study suggests that it is necessary to disperse the recognition and acknowledgement that the maintenance of the existing customers contributes more to boost repurchase intention when it is compared to the efforts to create new customers, particularly in the service industry. Meanwhile, the store itself can offer a unique environment that may influence the consumer's purchase decision. Consumers interact with store environments in the process of,virtually, all household purchase they make (Sarel 1981). Thus, store environments may encourage customers to purchase. The roles that store environments play are to provide informational cues to customers about the store and goods and communicate messages to stimulate consumers' emotions. The store environments differentiate the store from competing stores and build a unique service brand personality. However, the existing studies related to brand in the service industry mostly concentrated on the relationship between the quality of service and customer satisfaction, and they are mostly generalized while the connective studies focused on brand personality. Such approaches show limitations and are insufficient to investigate on the relationship between store environment and brand personality in the service industry. Accordingly, the study intends to identify the level of contribution to the establishment of brand personality made by the store's physical environments that influence on the specific brand characteristics depending on the type of service. The study also intends to identify what kind of relationships with brand personality exists with brand personality while being influenced by store environments. In addition, the study intends to make meaningful suggestions to better direct marketing efforts by identifying whether a brand personality makes a positive influence to induce an intention for repurchase. For this study, the service industry is classified into four categories based on to the characteristics of service: experimental-emotional service, emotional -credible service, credible-functional service, and functional-experimental service. The type of business with the most frequent customer contact is determined for each service type and the enterprise with the highest brand value in each service sector based on the report made by the Korea Management Association. They are designated as the representative of each category. The selected representatives are a fast-food store (experimental-emotional service), a cinema house (emotional-credible service), a bank (credible-functional service), and discount store (functional-experimental service). The survey was conducted for the four selected brands to represent each service category among consumers who are experienced users of the designated stores in Seoul Metropolitan City and Gyeonggi province via written questionnaires in order to verify the suggested assumptions in the study. In particular, the survey adopted 15 scales, which represent each characteristic factor, among the 42 unique characteristics developed by Jennifer Aaker(1997) to assess the brand personality of each service brand. SPSS for Windows Release 12.0 and LISREL were used in the analysis of data verification. The methodology of the structural equation model was used for the study and the pivotal findings are as follows. 1) The environmental factors ware classified as design factors, ambient factors, and social factors. Therefore, the validity of measurement scale of Baker et al. (1994) was proved. 2) The service brand personalities were subdivided as sincerity, excitement, competence, sophistication, and ruggedness, which makes the use of the brand personality scales by Jennifer Aaker(1997) appropriate in the service industry as well. 3) One-way ANOVA analysis on the scales of store environment and service brand personality showed that there exist statistically significant differences in each service category. For example, the social factors were highest in discount stores, while the ambient factors and design factors were highest in fast-food stores. The discount stores were highest in the sincerity and excitement, while the highest point for banks was in the competence and ruggedness, and the highest point for fast-food stores was in the sophistication, The consumers will make a different respond to the physical environment of stores and service brand personality that are inherent to the corresponding service interface. Hence, the customers will make a different decision-making when dealing with different service categories. In this aspect, the relationships of variables in the proposed hypothesis appear to work in a different way depending on the exposed service category. 4) The store environment factors influenced on service brand personalities differently by category of service. The factors of store's physical environment are transferred to a brand and were verified to strengthen service brand personalities. In particular, the level of influence on the service brand personality by physical environment differs depending on service category or dimension, which indicates that there is a need to apply a different style of management to a different service category or dimension. It signifies that there needs to be a brand strategy established in order to positively influence the relationship with consumers by utilizing an appropriate brand personality factor depending on different characteristics by service category or dimension. 5) The service brand personalities influenced on the repurchase intention. Especially, the largest influence was made in the sophistication dimension of service brand personality scale; the unique and characteristically appropriate arrangement of physical environment will make customers stay in the service environment for a long time and will lead to give a positive influence on the repurchase intention. 6) The store environment factors influenced on the repurchase intention. Particularly, the largest influence was made on the social factors of store environment. The most intriguing finding is that the service factor among all other environment factors gives the biggest influence to the repurchase intention in most of all service types except fast-food stores. Such result indicates that the customers pay attention to how much the employees try to provide a quality service when they make an evaluation on the service brand. At the same time, it also indicates that the personal factor is directly transmitted to the construction of brand personality. The employees' attitude and behavior are the determinants to establish a service brand personality in the process of enhancing service interface. Hence, there should be a reinforced search for a method to efficiently manage the service staff who has a direct contact with customers in order to make an affirmative improvement of the customers' brand evaluation at the service interface. The findings suggest several managerial implications. 1) Results from the empirical study indicated that store environment factors have a strong positive impact on a service brand personality. To increase customers' repurchase intention of a service brand, the management is required to effectively manage store environment factors and create a friendly brand personality based on the corresponding service environment. 2) Mangers and researchers must understand and recognize that the store environment elements are important marketing tools, and that brand personality influences on consumers' repurchase intention. Based on such result of the study, a service brand could be utilized as an efficient measure to achieve a differentiation by enforcing the elements that are most influential among all other store environments for each service category. Therefore, brand personality established involving various store environments will further reinforce the relationship with customers through the elevated brand identification of which utilization to induce repurchase decision can be used as an entry barrier. 3) The study identified the store environment as a component of service brand personality for the store's effective communication with consumers. For this, all communication channels should be maintained with consistency and an integrated marketing communication should be executed to efficiently approach to a larger number of customers. Mangers and researchers must find strategies for aligning decisions about store environment elements with the retailers' marketing and store personality objectives. All ambient, design, and social factors need to be orchestrated so that consumers can take an appropriate store personality. In this study, the induced results from the previous studies were extended to the service industry so as to identify the customers' decision making process that leads to repurchase intention and a result similar to those of the previous studies. The findings suggested several theoretical and managerial implications. However, the situation that only one service brand served as the subject of analysis for each service category, and the situation that correlations among store environment elements were not identified, as well as the problem of representation in selection of samples should be considered and supplemented in the future when further studies are conducted. In addition, various antecedents and consequences of brand personality must be looked at in the aspect of the service environment for further research.