本研究透過監視器在電視新聞發展歷程中的特殊性和新聞價值，以及監視器新聞的緣起和發展，結合電視新聞的相關理論和實證研究了解監視器影像和電視新聞媒體媒合以後，電視監視器新聞的敘事方式和其所再現的社會景觀以及社會文化意涵。 透過內容分析法，本研究發現，多數監視器新聞以目擊事件現場為「賣點」，呈現對犯罪事件和特殊奇觀的現場感，然而也有不少新聞在監視器鏡頭外，用特殊的剪輯和運鏡技巧或是帶有情緒性的口語配音進行後製，加深觀眾的「共感氛圍」。在「求真」之外，也追求在視聽訊息上的感官化，並透過選擇新聞題材以及後製加工帶給觀眾強大的視覺衝擊力和感染力。 監視器新聞主題中以暴力和犯罪為主，其次則為奇觀新聞。以感官化的手法呈現與社會安全相關的主題，以犯罪暴力為主題的監視器新聞人物，大多為社會上的邊緣團體，且多發生在都市區；奇觀新聞則以一般民眾為主，背景大多為非都市區；監視器新聞以一般市井小民為主要報導對象，公眾人物在監視器新聞裡十分罕見。監視器新聞再現的時空，突破新聞記者採訪佈線「時空」的限制。 監視器新聞的畫面來源和主要受訪者皆為警方，且多為採用「單面報導」的方式，也就是說，警方掌握監視器畫面以及享有對監視器畫面的主要詮釋權，顯示了公共攝影的社會控制和詮釋的不對等關係。在監視器新聞主題中也看到了符合社會奇觀的主題，「記錄不容錯過的精彩生活片段」似乎成了監視器在社會中扮演的另類角色。 當監視器與電視新聞媒合以後，電視新聞觀眾面對的是更多重、更奪目的真實形式。這些影像以「軟性化」或「衝突性」題材為主，而不是以訴諸理性或是傳達資訊的方式。監視器新聞帶出了公共危險的社會意象，對於邊緣團體化約、淺碟化的敘述，可能加深觀眾對於邊緣團體的刻板印象。整體而言，監視器新聞是一種去脈絡化的敘事形式，透過後製的音效和影像編輯，呈現緊張、懸疑和驚聳的氣氛，因此，監視器新聞所再現的都市空間形象是危險的、充滿不確定性的，為一種高社會犯罪率的隱喻。

本研究以銀髮族為主要的研究對象，採用脈絡分析法了解銀髮族於日常生活中的影像使用行為，經由在受訪者住所進行的深度訪談與行為觀察，探究數位影像與銀髮族的關連，日常生活的影像使用行為，與數位影像工具對銀髮族使用數位影像的影響。根據對銀髮族的影像使用行為與影像工具和情境故事的彙整，本研究歸納出三種銀髮族影像使用行為的核心價值，分別為分享、典藏和記錄。 　　此外研究中對使用影像行為的過程與不同使用工具的詮釋，也說明了不同影像工具因功能條件限制，為高齡使用者帶來的使用障礙與排斥使用的現象。根據本研究對銀髮族使用影像行為的活動脈絡，與針對情境故事進行的脈絡分析，所提出相關影像活動使用工具的設計建議與銀髮族影像服務未來的發展方向，將使未來的數位影像相關產品服務，更貼近年長使用者的生活需求。 / Through the contextual inquiries, understanding about the present usage and motivation of older people toward digital photography in their ordinary life are revealed. According to these scenarios from deep interviews and field observation, three different core values of photo usage behaviors to older people are identified, including sharing, archiving and recording. 　　Besides, the differences between photo usage behaviors and tools in these uses help us explain the obstacle of photo usage and the difficulties for adopting photography of mobile device by older people. Based on the knowledge above, proposing concrete directions of developing the applications of future digital photo technologies that actually fit in with older user’s needs are pointed out.

企業的永續經營需要不斷的成長與獲利，近幾年台灣市場成長不易，對於新市場的布局是許多企業面臨的重要課題。因所任職的公司，希望能以資訊代理商的條件，找到一個能開發出新的銷售通路的產品線，同時又能利用到既有已代理的資訊產品的優勢。這幾年雲端運算技術已成熟，儲存成本大幅降低，數位影像壓縮技術、網路頻寬與電腦效能大幅提升及手持裝置及應用程式普及化，從外在環境的趨勢，看到智慧影像監控及應用的成長機會。 本研究以個案公司為案例，探討一個成立30多年的資訊通路代理商，在決定投入智慧影像監控市場後，如何依自己的條件及瞭解競爭環境，用通路代理商的角度來擬定行銷策略。除了傳統類比轉成影像數位化的監控商機，對於雲端科技到物聯網、大數據分析、互動看板廣告行銷、行動科技等在智慧影像上的運用，希望能透過解決方案的整合找出新的市場機會及新的策略合作夥伴，並提出可具體商業化的營運模式。 對於智慧影像監控市場的應用，研究內容將列出現在及未來的主要應用內容，舉凡人流及車流分析、臉部及車牌辨識技術應用、熱感分析、智慧城市、消費者行為分析及互動式數位廣告等等，以資訊配銷商的利基點，找出商業模式，從使用者的不同需求，提供產品垂直整合上的規劃。在現有實體配銷機制，找出應用軟體開發商、資訊及網路監控等相關硬體設備建廠商、工程設計與建置服務等等的團隊合作機制。除了既有相互合作共同承攬生意的方式，也規劃透過B2B網路平台的行銷模式，建立案例行銷讓業主找到所需服務，吸引更多創新應用的公司加入合作的團隊，期能創造更多的互利多贏的營運模式。

熱紅外波段在遙感探測中佔有相當重要的地位，因其不受日夜條件限制，且因溫度變化時常具有與自然環境相關的特殊意義，使熱紅外影像可應用於測量、環境監控、都市開發、災害防治等領域。 在判釋遙測影像之前，通常必先確定各波段影像的幾何性質一致，若想將熱紅外影像與可見光影像套疊，須先率定蒐集熱影像之儀器，使影像受儀器本身的影響減到最低。本研究以FLIR-T360紅外線熱像儀為研究對象，探討熱像儀的成像特性，且嘗試率定與改正蒐集之熱影像。 率定熱像儀的實驗可分為幾何與輻射兩方面，幾何方面使用改良型的實地率定法，以求取熱像儀的內方位參數；輻射方面則使用實地調查法，求得控制點溫度，利用拍攝控制點蒐集多筆資料，擬合出輻射改正模型；本文亦展示熱影像幾何以及輻射改正後的成果。 / Thermal infrared data is important when conducting remote sensing investigation, for it could be acquired both in day and night. The change of temperature has characteristic significance of representing. So the thermal infrared images are used not only in the domain of surveying, but also in the environment monitoring, the urban development, and the disaster prevention. Before interpreting the remote sensing data, one would make sure that each image of bands has similar image geometry. Calibrating such geometry could prove that the effect from the lens distortion had been minimized. In such case, calibrated thermal images are necessary to guarantee that the image coordinates will correspond with the space coordinates as other bands. A thermal sensor, FLIR-T360 has been calibrated in this research. Two aspects of calibration executed are geometric and radiometric. A conventional calibrated template has been improved for using in the geometric aspect. The thermal sensor’s interior orientation elements were then found by using a field method. In the radiometric aspect, in situ method has been employed to determine temperatures of the chosen control points. The result of correction in geometric and radiometric aspect are also shown and discussed in this study.

三維城市模型之建置需求漸趨繁多，可提供都市規劃、城市導航及虛擬實境等相關應用，過去研究多以建置LOD2城市模型為主，且較著重於屋頂結構。近年來，逐漸利用垂直影像及傾斜影像作為原始資料，提供建物牆面之建置，並且，隨著無人機系統(Unmanned Aircraft System, UAS）發展，可利用其蒐集高解析度且高重疊垂直及傾斜拍攝之建物影像，並採影像密匹配技術產製高密度點雲，進而快速取得建物包含屋頂及牆面之三維資訊，而這些資訊可進一步提供後續建置LOD3建置層級之模型，而在建置前，首先須對資料進行特徵分析，萃取特徵點、線、面，進而提供建置模型所需之資訊。 因此，本研究期望利用密匹配點雲，計算其點雲特徵，並採用Mean Shift分群法（Comaniciu and Meer, 2002）萃取建物點雲資訊，並提供一最佳分群策略。首先，本研究將以UAS為載具，設計一野外率定場率定相機，並蒐集建物高重疊UAS影像密匹配產製高密度點雲，針對單棟建物高密度點雲，實驗測試點雲疏化程度後，依據疏化成果計算點雲特徵，並以此批點雲資料實驗測試Mean shift分群法（Cheng, 1995）中之參數，後設計分群流程以分離平面點群及曲面點群，探討分群成果以決定最佳分群策略。實驗結果顯示本研究提出之分群策略，可自動區分平面點群及曲面點群，並單獨將平面點群分群至各牆面。 / Unmanned Aerial System (UAS) offer several new possibilities in a wide range of applications. One example is the 3D reconstruction of buildings. In former times this was either restricted by earthbound vehicles to the reconstruction of facades or by air-borne sensors to generate only very coarse building models. UAS are able to observe the whole 3D scene and to capture images of the object of interest from completely different perspectives. Therefore, this study will use UAS to collected images of buildings and to generate point cloud from dense image matching for modeling buildings. In the proposed approach, this method computes principal orientations by PCA and identifies clusters by Mean shift clustering. Analyze the factors which can affect the clustering methods and try to decrease the use of threshold, and this result can cluster the façade of buildings automatically and offer the after building reconstruction for LOD3.

「家」是人類生活的重心，居家影像監控設備的需求來自於家庭用戶想要掌握居家環境安全現況。相對於商業影像監控的應用，居家影像監控設備安裝的複雜度需要較低。因此居家影像監控市場以簡易安裝、遠端監控為主要的發展趨勢。 網路攝影機(IP Camera)具有數位化及網路化的特色，掌握寬頻網路的電信業者積極為影像監控市場創造新興的居家應用情境。許多傳統影像監控產品製造商為因應居家影像監控的潮流，也紛紛推出產品因應。然而電信業者及傳統影像監控業者在居家影像監控的市場都沒有得到很大的成功。個案公司創立於2009年，在2012年所推出的第一代產品，一開始只在網路上銷售，卻在2012、2013席捲美國市場，成為美國居家影像監控產品的第一品牌。 本研究探討之研究問題包括: (一)數位化及網際網路的普及對影像監控產品設計之影響、(二)行動裝置的普及對影像監控產品設計之影響、(三)個案公司提升消費者認知價值之產品創新策略。 本研究採用個案研究方法，首先列出客戶所重視的產品要素，以產品關鍵要素為橫軸客戶對個案產品的認知價值為縱軸描繪出曲線圖，比較個案公司產品與競爭對手的產品價值曲線，可解讀出其策略上的差異點。最後運用藍海策略思維，重塑和創新價值曲線以產生新的策略意義。 本研究發現，數位科技進步及網際網路的普及降低了使用影像監控產品的門檻，因而使居家影像監控產品得以被大量採用。而移動裝置的普及改變了消費者使用影像監控產品的方式，使用者的體驗主要來自於手機App的操作經驗，與過去在個人電腦上的使用經驗完全不同。個案公司以解決使用者痛點作為提升消費者認知價值之產品創新策略，值得居家影像監控業者未來產品規劃參考。 / Home is the center of human life, home video surveillance equipment demand from home users want to master the security status of the home environment. With respect to the commercial video surveillance applications, home video surveillance equipment requires low complexity of the installation. Therefore, the main trend of home video surveillance is easy installation and remote monitoring. IP Camera has digitized and network-oriented features, Internet carriers create new application scenarios for home video surveillance market. Many traditional video surveillance equipment manufacturers to cope with the trend of home video surveillance have also introduced products in response. However, carriers and traditional video surveillance industry in the home video surveillance markets have not been very successful. Founded in 2009, Dropcam Inc. launched the first generation of products in 2012, selling only on the Internet at the beginning, became the top brand of home video surveillance products in United States in 2013. This study try to answer three questions: (1) The popularity of digital technology and the Internet's impact on the design of video surveillance products, (2) The impact of the popularity of mobile devices on the design of video surveillance products, (3) Dropcam’s product innovation strategy to enhance consumer perceived value of the product. This study used a case study approach. Comparing the product value curve of Dropcam's products and its competitor’s product can interpret difference of strategy. Finally, the use of blue ocean strategy thinking, remodeling and innovation to create a new value curve strategic importance. The study found that the popularity of digital technology and the Internet's progress reducing the threshold to use of video surveillance products, thus making home video surveillance products to be widely adopted. The popularity of mobile devices has changed the way consumers use video surveillance products. Dropcam to resolve user’s pain points to enhance consumer awareness of the value of a product. It is worth for coming home video surveillance maker’s reference.

商標是一種藉由圖像或是混和圖像與文字存在的標誌，經由特定的符號或是顏色所組成，利用圖像的組成、配置、形狀、顏色、混合、字體、字體顏色等視覺元素將會帶給人們不同的視覺感受。 過去的研究中，對於視覺元素在商標中扮演的角色偏向質化的探討，通常多利用使用者測試的方法找到設計元素與商標的相關度，較少應用電腦視覺對於圖像量化分析的方法，本研究的目的在於利用各種視覺特徵的計算方式，分析各種商標中視覺元素的組成，包含商標中圖像的複雜度、和諧度、組成重複度等相關量化指標。 藉由大量透過網路上收集的商標進行分析後，可發現商標普遍具有低複雜度、高和諧度、低重複度的設計特性，本論文最後試著以商標獨特性指標代替商標辨識度以驗證本論文設計的分析方法可行性。由於在電腦視覺領域中相關於商標美學的研究並不常見，本論文亦希望能對電腦視覺分析應用在設計或美學的領域進行先導性的研究。 / A logo is a mark composed of graph or a combination of text and graph. Typical visual elements in a logo design such as layout, shape, color (foreground and background), composition, and typeface. The graphical mark can exhibit interesting properties by mixing the elements in creative ways. Most previous researches regarding the role of visual elements in logo design are of qualitative nature. In this thesis, we propose to incorporate visual feature extraction and analysis algorithms commonly utilized in computer vision to compute proper index and investigate key visual elements in logo design, including complexity, harmony and repetition. After analyzing large amount of logos collected from the internet, we find out that most logos are of low complexity, high balance and exhibit some degree of repetition. We propose a new measure of “distinctiveness” and investigate its relationship with to the aforementioned properties. We hope that the results obtained in thesis serve as a catalyst to motivate further research in applying computer vision methods to the area of aesthetics and design.

以身體知覺作為出發點，將疼痛經驗帶入虛擬影像中，藉此探討身體知覺的運作及兩者間的關聯性，蒐集相關文獻資料與實際作品的分析，深入瞭解如何在虛擬世界透過身體知覺建立自我存在，最後，以創作行動去探討虛擬影像與身體知覺，並以展覽的方式，藉由作品與人之間的互動，提供進一步的思考。 透過文獻資料的彙整瞭解關於身體知覺的形成、記憶經驗、身體知覺與「我的身體」、影像的演進、虛擬影像等加以蒐集與彙整，從中得知，進以瞭解虛擬影像中身體知覺的鍵結。接下來，透過相關案例的分析，與理論相互驗證，讓自己在創作的脈絡和歷程有更清楚的思維。最後，整理出自己對身體知覺及虛擬影像的觀點，進而執行下一階段的創作行動。 本研究以創作方式探討「身體知覺－虛擬影像」，透過擴增實境藝術的創作行動，期許觀者在體驗作品時，能透過虛擬影像，喚起個人的身體知覺的運作，進而引導觀者對虛擬與現實間的「自我存有」有更大的想像與討論。 / The motivation of this study is, by combining the pain experience with the virtual images, to explore the association among operations of physical consciousness, pain experiences and synthesized virtual images. The ways to use physical consciousness when building self-existence in virtual images are investigated by collecting relevant literature and performing analysis of empirical works. Finally, the overall concepts are implemented and realized in the form of an exhibition which facilitates the reflections of visitors after interacting with these virtual images provided in the exhibition. The overall research activity begins by compiling the pieces of literature. Specifically, to understand, collect, and aggregate the concepts of physical consciousness and its relationship with "My Body," memorable experience, image evolution, and virtual images. Next, via the analysis of the related cases and the mutual verification of the theories, the contexts and thinking of the process of artifact creation are clarified. Lastly, this research systematizes a unique and novel view of physical consciousness and virtual Images, which is helpful for the design activity in the next stage. Consequently, the main focus of this study is to explore the concepts of physical consciousness of virtual images in a novel way. By amplification of augmented reality art, it is anticipated that the audiences evoke physical consciousness operations of themselves in the exhibition and that the research results enable bigger imagination and discussion with virtual and reality “Self-existence.”

隨著智慧型手機的普及，在移動裝置上直接處理圖像的需求也大幅增加，故對於影像特徵描述子的要求，除了要表現出區域特徵的穩健性，同時也要維持良好的特徵比對效率與合理的儲存空間。過去所提出的區域影像特徵描述子建構方法之中，LIOP方法具有相當不錯的表現力，但其特徵描述子維度會隨著點群取樣數量的提高而以倍數增加，因此本研究提出Dynamic Local Intensity Order Relations (DLIOR)特徵描述子建構方法，利用LIOR方法探討點群中點與點之間的關係，減緩其維度增長幅度；透過動態設定像素差距門檻值，處理影像間像素差距分佈不均的問題，並使用線性轉換、點對歐幾里德距離等方式，重新定義描述子欄位的權重設定。經過實驗證實，DLIOR方法能夠使用比LIOP方法更少的維度空間，描述更多點群數的特徵資訊，並且具有更高的特徵比對能力。 / With the popularity of smart phones, the amounts of images being captured and processed on mobile devices have grown significantly in recent years. Image feature descriptors, which play crucial roles in recognition tasks, are expected to exhibit robust matching performance while at the same time maintain reasonable storage requirement. Among the local feature descriptors that have been proposed previously, local intensity order patterns (LIOP) demonstrated superior performance in many benchmark studies. As LIOP encodes the ranking relation in a point set (with N elements), however, its feature dimension increases drastically (N!) with the number of the neighboring sampling points around a pixel. To alleviate the dimensionality issue, this thesis presents a local feature descriptor by considering pairwise intensity relation in a pixel group, thereby reducing feature dimension to the order of C^N_2. In the proposed method, the threshold for assigning order relation is set dynamically according to local intensity distribution. Different weighting schemes, including linear transformation and Euclidean distance, have also been investigated to adjust the contribution of each pairing relation. Ultimately, the dynamic local intensity order relations (DLIOR) is devised to effectively encode intensity order relation of each pixel group. Experimental results indicate that DLIOR consumes less storage space than LIOP but achieves better feature matching performance using benchmark dataset.

除了文字訊息，張貼相片也是臉書使用者常用的功能，這些上傳的照片種類繁多，可能是自拍照、風景照、或食物照等等，本論文的研究以影像分析為出發點，探討相片內容跟發佈者間之關係，希望藉由相片獲得的資訊，輔助分析使用者樣貌。 本研究共收集32位受測者上傳至臉書的相片，利用電腦視覺技術分析圖像內容，如人臉偵測、環境識別、找出影像上視覺顯著的區域等，藉由這些工具所提供的資訊，將照片加註標籤，以及進行自動分類，並以此兩個層次的資訊做為特徵向量，利用階層式演算法進行使用者分群，再根據實驗結果去分析每一群的行為特性。 透過此研究，可對使用者進行初步分類、瞭解不同的使用者樣貌，並嘗試回應相關問題，如使用者所張貼之相片種類統計、不同性別使用者的上傳行為、 依據上傳圖像內容，進行使用者樣貌分類等，深化我們對於臉書相片上傳行為的理解。 / Apart from text messages, photo posting is a popular function of Facebook. The uploaded photos are of various nature, including selfie, outdoor scenes, and food. In this thesis, we employ state-of-the-art computer vision techniques to analyze image content and establish the relationship between user profile and the type of photos posted. We collected photos from 32 Facebook users. We then applied techniques such as face detection, scene understanding and saliency map identification to gather information for automatic image tagging and classification. Grouping of users can be achieved either by tag statistics or photo classes. Characteristics of each group can be further investigated based on the results of hierarchical clustering. We wish to identify profiles of different users and respond to questions such as the type of photos most frequently posted, gender differentiation in photo posting behavior and user classification according to image content, which will promote our understanding of photo uploading activities on Facebook.