Pedestrian detection has been an active research area for computer vision in recently years. It has many applications that could improve our lives, such as video surveillance security, auto-driving assistance systems, etc. The approaches of pedestrian detection could be roughly categorized into two categories, shape-based approaches and appearance-based approaches. In the literature, most of approaches are appearance-based. Shape-based approaches are usually integrated with an appearance-based approach to speed up a detection process. In this thesis, I propose a shape-based pedestrian detection framework using the geometric features of human to detect pedestrians. This framework includes three main steps. Give a static image, i) generating the edge image of the given image, ii) according to the edge image, extracting the basic polylines, and iii) using the geometric relationships among the polylines to detect pedestrians. The detection result obtained by the proposed framework is promising. There was a comparison made of this proposed framework with the algorithm which introduced by Dalal and Triggs [7]. This proposed algorithm increased the true-positive detection result by 47.67%, and reduced the false-positive detection number by 41.42%.

Woodruff (1997) 認為企業若沒有由建構滿意度的顧客價值 (customer value) 中做更為深入的了解，則顧客的意見將無法完全引導管理者研擬競爭策略。因此Woodruff (1997) 進而主張顧客價值才是企業當前最主要競爭優勢的來源，而非滿意度而已。Peterson (1995) 的研究指出，透過經驗所給予顧客的價值，是促使顧客願意與廠商進一步建立起長久關係的驅動因子。Spiegelman (2000) 也建議：「廠商若希望能夠將第一次消費的造訪者，進而轉變成為重複購買的顧客，則廠商必須在消費體驗的過程中不斷的傳遞價值」。換言之，體驗價值 (experiential value) 可視為提高顧客忠誠的最佳利器 (Stoel, Wickliffe and Lee, 2004)。再者，Babin, Darden, and Griffin (1994) 認為體驗價值是消費經驗後的主要結果，若研究者沒有確實掌握所知覺的體驗價值為何，則無法清楚了解消費者的消費經驗全貌。然而體驗價值雖然對於行銷研究與管理者相當重要，但有關消費者體驗價值的探討，主要都限制在網路購物的人機互動情境。關於線上人際互動情境中，將可能產生何種體驗價值，學者就較少進行探究 (Mathwick, 2002)。 Pine and Gilmore (1999) 在體驗經濟《Experiential Economics》一書中曾指出，消費者之所以能夠形成難忘且有價值的體驗，關鍵乃在於廠商是否能夠設計一個使消費者完全融入，且如同身歷其境的感受。換言之，引發消費者沈浸當下的消費情境，成為企業傳遞體驗價值給消費者的關鍵因素所在。但很遺憾的，沈浸與體驗價值的關係，過去研究較少深入的分析與探討，而且先前的研究情境卻也僅限於線上搜尋的人機互動經驗 (Mathwick and Rigdon, 2004)，忽略了人際互動的體驗才是消費者最為渴望的經驗 (Spiegelman, 2000)。因此在今日人們相當渴望透過網路進行人際接觸的同時，研究更應深入討論與分析，在線上人際互動情境中，沈浸 (flow) 與各種體驗價值 (experiential value) 的關係。 基於上述，研究將選擇以同時具有人際與人機互動的線上遊戲為主要研究情境，藉此以補足缺乏探討人際與人機互動共有的沈浸經驗之缺口，同時也進一步將沈浸概念擴大其應用的範疇，不在只限於人與特定事物間的沈浸研究。 在研究方法方面，有鑑於人際與人機互動的沈浸概念必須重新被審視並釐清 (Huang, 2006)，並且考量消費者的沈浸狀態是具有動態且連續發生一段時間的特性，同時也由於沈浸本身是一種內心深處的感受，若訪談過程中沒有任何憑據可提供受訪者作事後的回憶，則受訪者將很難描述沈浸當時發生的所有感受與心路歷程 (Csikszentmihalyi and Csikszentmihalyi, 1988)，基於此，本研究選擇能夠幫助受訪者回憶起所有心路歷程的自發性導引法 (auto-driving) (Belk and Kozinets, 2005)，為探討沈浸的質化研究方法，如此才能藉此重新釐清在人際與人機互動情境中，消費者沈浸的定義與構面。更進一步的，由於能夠更清楚掌握沈浸的本質，也才能夠使得研究者可以更為明確的探究出引發沈浸產生的人際與人機互動因子以及在沈浸歷程中消費者所知覺體驗價值類型。 經訪談17位受訪者後，不僅探究出在人際與人機互動媒體情境下的沈浸成份，同時也依據沈浸所包含的特質，對沈浸下了如下的定義：「所謂沈浸是指消費者產生情境推想、整合思維、具象化、情緒感染與情緒激發的狀態。」其中「情境推想」，是消費者猜想線上其他消費者的想法、意圖與動向所釀成；「整合思維」是來自消費者多方思索回應他人策略與執行策略效果所促成；「具象化」則是消費者將線上他人的表情或揣摩想像內容予以圖像化所形塑而成的狀態；「情緒感染」的狀態則源自消費者感同他人情緒的效果；「情緒激發」是來自消費者將個人內心的情緒，藉由肢體或表情予以宣洩的狀態。另外，從消費者的自我沈浸描述內容中，研究得知，前述這五種沈浸成份，其彼此間存有因果關係，而這樣的研究結果，是先前沈浸研究未能確實發現的。 其中，情緒激發的形成深受情緒感染與整合思維兩元素直接影響，又具象化分別會直接影響情緒感染與整合思維兩成份的產生。最後情境推想也會分別引發具象化、整合思維、情緒感染等沈浸成份的產生。 更進一步，研究也根據訪談內容結果得知，影響沈浸的前置因子可分為人際與人機互動兩種類型的因素，其中在人際因素方面，包含具有二元對立目標設定的競玩，以及源自環境成份所營造出探索趣味的嬉玩。同時人際與人機互動情境中所引發的人際互動競爭性與親和性，可營造出競玩氣氛。而人際互動中的不確定性與嘲弄則是構成嬉玩的主要成份。最後影響消費者沈浸經驗的人機互動因子包括驚奇性、因果性、生動性等三種因素。因此這將可以給予研究者與管理者，在設計吸引消費者融入購買或消費情境時的重要參考。 另外，訪談內容的結果也顯示，人際與人機互動的沈浸經驗不只是一種最佳互動消費經驗 (Novak and Hoffman, 1996; Privette and Bundrick, 1987)，同時它包含了許多豐富且多元的體驗價值 (Mathwick, et al., 2001)。換言之，當消費者全心投入在情境推想、整合思維、具象化、情緒感染與情緒激發等任一種活動時，都可以知覺到成就感、尊重、趣味性等這三種價值類型。隨著沈浸經驗本身具有多元且豐富的體驗價值，使得參與線上人際互動的消費者，更因此希望再次透過如此的經驗獲取價值。也因此，沈浸經驗提高了消費者願意再次經歷的意圖。 在經過第二階段研究中一系列沈浸量表的發展與檢測分析後，研究結果顯示，所發展的沈浸量表與體驗量表不論是在探索性因素分析、一階驗證性因素分析與二階驗證性因素分析都具備很好的信度與效度。不僅如此，藉由結構方程式模式的統計分析，研究進一步驗證五種沈浸成份間、沈浸與體驗價值間、五種沈浸成份與體驗價值間、沈浸與持續消費行為間以及五種沈浸成份與持續消費行為間的因果關係。而研究結果顯示，不僅整體模式的配適度達評鑑要求的水準，同時每一個變數彼此間的因果關係也都達顯著。 / Woodruff (1977) maintains that customers’ opinions can lead managers to plan competitive strategies if enterprises can have a profound understanding and analysis of customer value, which influences on the formation of customer satisfaction. Accordingly, it’s Woodruff’s contention that the primary source of competitive edge among present-day enterprises isn’t just concerned with “customer satisfaction”, but with “customer value” as well. According to Peterson’s research (1995), the experience-based value bestowed upon customers is an impetus to customers’ desire to develop a long-term relationship with enterprises. Furthermore, Spiegelman (2000) also suggests that enterprises have to incessantly deliver value to customers in their consumption process if enterprises expect to turn customers purchasing for the first time into those making purchase over and over again afterwards. In other words, experiential value can be seen as the best way to enhance customer loyalty (Stoel, Wickliffe, and Lee 2004). What’s more, Babin, Darden, and Griffin (1994) think that experiential value is the major result of consumption experience, and that observers won’t get a clear, and panoramic picture of the consumption experience in case they can’t tell exactly what the perceived experiential value is. However, though experiential value plays an integral part between managers and marketing research, discussions on customer’s experiential value are primarily confined to the online-shopping machine-interactivity context. As for online person-interactivity context, scholars are to put less emphasis on what experiential value can be generated and delivered to customers under such a context (Mathwick 2002). According to the book Experiential Economics, written by Pine and Gilmore (1999), Pine and Gilmore indicate that whether enterprises can create a context for customers to fully engage themselves in and live vicarious with is the key to the formation of customer’s unforgettable and valuable experience. To put it differently, the consumption environment which can prompt customer’s flow in the present plays a pivotal role in helping enterprises deliver experiential value to their customers. However, it’s a pity that in-depth discussions and analyses of the relationship between experiential value and flow are usually overlooked by previous researchers. Besides, previous research context is limited to online-searching machine-interactivity experience (Mathwick and Rigdon 2004), neglecting that person-interactivity experience is the one that customers yearn for the most (Spiegelman 2000). Therefore, in-depth discussions and analyses of the relationship between various experiential values and flow in online person-interactivity context should be made, especially in modern times when people are desperate for personal exposure through the Internet. As aforementioned, by choosing online games with both person-interactivity and machine-interactivity as the primary research context, the research aims to make up for the lack of discussions on flow experience shared by person-interactivity and machine-interactivity contexts. In the meanwhile, the research puts concepts of flow to a wide range of use, not just in the flow research between people and specific things. As far as the research method is concerned, the research takes the facts into consideration that concepts of flow in person-interactivity and machine-interactivity contexts need re-examining and clarifying (Huang 2006), and that customer’s flow conditions are dynamic and capable of lasting for a period of time consecutively. Moreover, since the flow is a feeling in the recesses of mind, interviewees might have a hard time delineating the course of thought developments and feelings in the flow experience if there are no reminders in the interview process for them to recall afterwards (Csikszentmihalyi and Csikszentmihalyi 1988). Considering the above-mentioned factors, the research chooses a method called “auto-driving”, able to help interviewees recall their courses of thought developments and feelings in their consumption process (Belk and Kozinets 2005), as the qualitative research method for exploring what flow is. In this way, the definition and dimensions of customer flow experience in person-interactivity and machine-interactivity contexts are likely to be clarified. What’s more, researchers can get a more explicit picture of what types of experiential value that customers would perceive in the process of flow are due to the fact that such a method will better the understanding of the essence of flow. Furthermore, once the elements of the flow have been confirmed, the researcher may also clearly ascertain what kinds of the person-interactivity and machine-interactivity factors triggering flow. After the first phase interviews, the present study not only finds out components of flow, but also defines flow as consumers’ state of inferring thinking, integrated thinking, visualization, emotional contagion and emotional arousal. Besides, according to the content of consumers’ self-description about flow experience, the study also found that causal relationships among the five elements of flow which were not found in the previous flow studies. For example, emotional contagion and integrated thinking influenced simultaneously emotional arousal and visualization influenced simultaneously emotional contagion and integrated thinking. Finally, inferring thinking directly influenced visualization, integrated thinking, and emotional contagion. Furthermore, the researcher identifies both person-interactivity and machine-interactivity factors that influence flow in base on the result of interviewees’ description about flow experience. Also, there are ludus which comes from the design of winning or losing and paidia which comes from exploring interesting content in person-interactivity factors. At the same time, the elements of ludus are competition and affiliation, and the elements of paidia are uncertainty and teasing. Finally, the machine-interactivity factors which influence flow include surprise, causality, and vividness. These findings would be practical implications for design consumers’ flow experience in further for the researcher and the management in service marketing. The result of the interviews also proves that flow experience with both person-interactivity and machine-interactivity is not only the optimal interactive consuming experience (Novak and Hoffman, 1996; Privette and Bundrick, 1987), but also delivers the multiple and rich experiential value to consumers. (Mathwick, et al., 2001). On the other word, consumers would perceive experiential value of achievement, reputation, and playfulness when they act with total involvement in one of the inferring thinking, integrated thinking, visualization, emotional contagion, or emotional arousal. Because of flow experience including multiple and rich experiential value, consumers in online person-interactivity would like to have the same flow experience in order to perceive these experiential value again. Therefore, flow experience positively influences re-patronage intention. The result of flow scale development and detection and analysis in the second step of this study shows flow scale is validity and reliability base on the exploratory factor analysis, the first confirmatory factor analysis and the second confirmatory factor analysis. The study further confirms causal relationships among the five elements of flow, causal relationships between flow and experiential value, causal relationships among the five elements of flow and experiential values, causal relationships between flow and re-patronage intention, and causal relationships among the five elements of flow and re-patronage intention by the statistic analysis of structure equation modeling.

Devices for measuring the dynamic load and vibration of certain parts of the bodywork or parts of other parts of the vehicle are made using accelerometers and measuring instruments IMC. It must be simply installed into the interior of the vehicle so that it is not necessary to remove any parts of the interior and to avoid damage to all parts of the interior. The preparation must also withstand the considerable dynamic load generated by the harder operation tests.