Remote sensors and unmanned aerial vehicles (UAVs) have the potential to dramatically improve infrastructure health monitoring in terms of accuracy of the information and frequency of data collection. UAV automation has made significant progress but that automation is also creating vast amounts of data that needs to be processed into actionable information. A key aspect of this work is the optimization (not just automation) of data collection from UAVs for targeted planning of mission objectives. This work investigates the use of camera planning for Structure from Motion for 3D modeling of infrastructure. Included in this thesis is a novel multi-scale view-planning algorithm for autonomous targeted inspection. The method presented reduced the number of photos needed and therefore reduced the processing time while maintaining desired accuracies across the test site. A second focus in this work investigates various set covering problem algorithms to use for selecting the optimal camera set. The trade-offs between solve time and quality of results are explored. The Carousel Greedy algorithm is found to be the best method for solving the problem due to its relatively fast solve speeds and the high quality of the solutions found. Finally, physical flight tests are used to demonstrate the quality of the method for determining coverage. Each of the set covering problem algorithms are used to create a camera set that achieves 95% coverage. The models from the different camera sets are comparable despite having a large amount of variability in the camera sets chosen. While this study focuses on multi-scale view planning for optical sensors, the methods could be extended to other remote sensors, such as aerial LiDAR.

Remote sensors and unmanned aerial vehicles (UAVs) have the potential to dramatically improve infrastructure health monitoring in terms of accuracy of the information and frequency of data collection. UAV automation has made significant progress but that automation is also creating vast amounts of data that needs to be processed into actionable information. A key aspect of this work is the optimization (not just automation) of data collection from UAVs for targeted planning of mission objectives. This work investigates the use of camera planning for Structure from Motion for 3D modeling of infrastructure. Included in this thesis is a novel multi-scale view-planning algorithm for autonomous targeted inspection. The method presented reduced the number of photos needed and therefore reduced the processing time while maintaining desired accuracies across the test site. A second focus in this work investigates various set covering problem algorithms to use for selecting the optimal camera set. The trade-offs between solve time and quality of results are explored. The Carousel Greedy algorithm is found to be the best method for solving the problem due to its relatively fast solve speeds and the high quality of the solutions found. Finally, physical flight tests are used to demonstrate the quality of the method for determining coverage. Each of the set covering problem algorithms are used to create a camera set that achieves 95% coverage. The models from the different camera sets are comparable despite having a large amount of variability in the camera sets chosen. While this study focuses on multi-scale view planning for optical sensors, the methods could be extended to other remote sensors, such as aerial LiDAR.

電影是門用畫面說故事的藝術，除了劇情上的編排，導演也必須思考如何運用鏡頭配置和運鏡技巧來渲染氣氛並傳達故事。電影拍攝製作上一直都是件費時費力的工程，儘管現在有不少電影後製工具，但專注在根據電影內容提升或改善拍攝手法的工具卻不多。本研究目標為開發智慧型電腦動畫攝影編輯輔助系統及互動操作平台，透過圖示化攝影機拍攝的結果作為選項的介面和推薦系統，讓使用者可以快速簡單的設置虛擬攝影機，配合智慧型回饋提醒系統檢查各鏡頭間是否違反拍攝規則，以達到輔助攝影初學者的目的，提供創新有效的動畫電影拍攝輔助工具。我們透過實驗讓不同攝影背景經驗的使用者操作，以驗證我們系統的可用性。 / Movie is the art of "storytelling." In addition to arranging story elements in a movie, a di-rector must also consider how to present the story by shots arrangement and operations. Filmmaking is a time-consuming process. Although there are many post-production tools available in the market, it is rare to find a tool focusing on facilitating shot arrangement to improve the quality of a movie. In this work, we have developed an intelligent camera editing system for computer animation, in which users can easily set up virtual cameras through se-lecting shot icons recommended by the system. It can also provide intelligent feedbacks to novice users and check if the shots selected by the users violate the rules in virtual cinema-tography. In order to show that the system is an innovative and effective tool for making an animation film, we have conducted an evaluation study by inviting participants with different photographic backgrounds to experience the system and verify the usability of our system.

The objective of this thesis is to model and solve the problem of placing thermal imaging camera for monitoring piles of combustible bio-fuels. The cameras, of different models, can be mounted at discrete heights on poles at fixed positions and at discrete angles, and one seeks camera model and mounting combinations that monitor as much of the piles as possible to as low cost as possible. Since monitoring all piles may not be possible or desired, due to budget or customer constrains, the solution to the problem is a set of compromises between coverage and cost. We denote such a set of compromises a frontier. In the first part of the thesis a way of modelling the problem is presented. The model uses a discrete formulation where the area to monitor is partitioned into a grid of cells. Further, a pool of candidate camera placements is formed, containing all combinations of camera models and mounting positions. For each camera in this pool, all cells monitored are deduced using ray-casting. Finally, an optimization model is formulated, based on the pool of candidate cameras and their monitoring of the grid. The optimization model has the two objectives of minimizing the cost while maximizing the number of covered cells. In the second part, a number of heuristic optimization algorithms to solve the problem is presented: Greedy Search, Random Greedy Search, Fear Search, Unique Search, Meta-RaPS and Weighted Linear Neighbourhood Search. The performance of these heuristics is evaluated on a couple of test cases from existing real world depots and a few artificial test instances. Evaluation is made by comparing the solution frontiers using various result metrics and graphs. Whenever practically possible, frontiers containing all optimal cost and coverage combinations are calculated using a state-of-the-art solver. Our findings indicate that for the artificial test instances, the state-of-the-art solver is unmatched in solution quality and uses similar execution time as the heuristics. Among the heuristics, Fear Search and Greedy Search were the strongest performing. For the smaller real world instances, the state-of-the-art solver was still unmatched in terms of solution quality, but generating the frontiers in this way was fairly time consuming. By generating the frontiers using Greedy Search or Random Greedy Search we obtained solutions of similar quality as the state-of-the-art solver up to 70-80% coverage using one hundredth and one tenth of the time, respectively. For the larger real world problem instances, generating the frontier using the state-of-the-art solver was extremely time consuming and thus sometimes impracticable. Hence the use of heuristics is often necessary. As for the smaller instances, Greedy Search and Random Greedy Search generated the frontiers with the best quality. Often even better full coverage solutions could be found by the more time consuming Fear Search or Unique Search. / Syftet med detta examensarbete är att modellera och lösa kameraplaceringsproblemet då IR-kameror ska användas för brandövervakning av fastbränslehögar. Problemet består i att givet ett antal kamera modeller och monteringsstolpar bestämma de kombinationer av placeringar och modeller sådana att övervakningen av högarna är maximal, för alla möjliga kostnadsnivåer. I den första delen av examensarbetet presenteras en modell för detta kameraplaceringsproblem. Modellen använder sig av en diskret formulering, där området om ska övervaras är representerad av ett rutnät. De möjliga kameravalen beskrivas med en diskret mängd av möjliga kameraplaceringar. För att utröna vilka celler inom rutnätet som en kameraplacering övervakar används metoden ray-casting. Utifrån mängden av möjliga kameraplaceringar kan en optimeringsmodell med två målfunktioner formuleras. Målet i den första målfunktionen är att minimera kostnaden för övervakningen och i den andra att maximera storleken på det övervakade området. Utgående från denna modell presenteras därefter ett antal algoritmer för att lösa modellen. Dessa är: Greedy Search, Random Greedy Search, Fear Search, Unique Search, Meta-RaPS och Weighted Linear Neighbourhood Search. Algoritmerna utvärderas på två konstgjorda testproblem och ett antal problem från verkliga fastbränslelager. Utvärderingen baseras på lösningsfronter (grafer över de icke-dominerade lösningarna med de bästa kombinationerna av kostnad och täckning) samt ett antal resultatmått som tid, lägsta kostnad för lösning med full täckning, etc... Vid utvärderingen av resultaten framkom att för de konstgjorda testinstanserna presterade ingen av heuristikerna jämförbart med en standardlösare, varken i termer av kvalitén på lösningarna eller med hänsyn tagen till tidsåtgången. De heuristiker som presterade bäst på dessa problem var framförallt Fear Search och Greedy Search. Även på de mindre probleminstanserna från existerande fastbränslelager hittade standardlösaren optimala lösningsfronter och en lösning med full täckning, men tidsåtgången var här flera gånger större jämfört med vissa av heuristikerna. På en hundra- respektive en tiondel av tiden kan Greedy Search eller Random Greedy Search heuristikerna finna en lösningsfront som är jämförbar med standardlösare, upp till 70-80% täckning. För de största probleminstanserna är tidsåtgången vid användning av standardlösare så pass stor att det i många fall är praktiskt svårt att lösa problemen, både för att generera fronten och att hitta en lösning med full täckning. I dessa fall är heuristiker oftast de enda möjliga alternativen. Vi fann att Greedy Search och Random Greedy Search var de heuristiker som, liksom för de mindre probleminstanserna, genererade de bästa lösningsfronterna. Ofta kunde dock en bättre lösning för full täckning hittas med hjälp av Fear Search eller Unique Search.

在互動敘事(Interactive Storytelling)的應用中，適當的攝影機規劃能幫助我們呈現虛擬世界中所發生的故事。在本研究中，我們設計了一個可以讓使用者設計互動敘事的應用平台－IMStory。針對故事創作，我們提供了一個故事腳本的描述語言及其剖析器，當使用者撰寫好互動故事之後，系統便能夠根據故事情境內容及與使用者互動的結果產生出符合情境的自動攝影機規劃系統。在此系統中，我們建立了一個能夠讓攝影機理解故事腳本的關係模型，建立虛擬攝影機組態與「故事情境」間的對應關係，即時找出更能表達當時情境的拍攝方式與架設位置。最後，我們設計了一個場景劇本進行實驗，在實驗中，我們的系統能夠即時因應場景中角色物件的位置作出即時的攝影機規劃，並且能夠配合互動環境中改變的情境參數而使用適合的攝影模組，產生出符合攝影學法則且賦有敘事能力的鏡頭。透過我們的方法，希望能提供一個更加有敘事能力的互動敘事平台。 / In an 3D interactive storytelling system, virtual camera is the key for us to understand what happens in the virtual world. In this thesis, we have designed an intelligent camera planning system for interactive storytelling, in which story plots are influenced by the user’s actions. Since the story flow cannot be determined in advance, it is essential to utilize real-time camera control to express the story for given spatial relationships between characters and objects. A script language and its parser were designed for our storytelling system (IMStory) to describe events in the story as well as the contexts associated with the events to model the properties of a story for camera control. We have developed a camera planning system by mapping contexts parameters into appropriate camera control parameters. We have implemented the 3D interactive storytelling system and demonstrated its capabilities with several examples. The camera planning system is shown to perform in real time, and the generated shots are more expressive in establishing the relation between camera configurations and story context.