Thesis (M.A.)--Ohio State University, 1968. / Includes bibliographical references (leaves 66-68). Available online via OhioLINK's ETD Center.

In today’s fast paced world, as the number of stations of television programming offered is increasing rapidly, time accessible to watch them remains same or decreasing. Sports videos are typically lengthy and they appeal to a massive crowd. Though sports video is lengthy, most of the viewer’s desire to watch specific segments of the video which are fascinating, like a home-run in a baseball or goal in soccer i.e., users prefer to watch highlights to save time. When associated to the entire span of the video, these segments form only a minor share. Hence these videos need to be summarized for effective presentation and data management. This thesis explores the ability to extract highlights automatically using MPEG-7 features and hidden Markov model (HMM), so that viewing time can be reduced. Video is first segmented into scene shots, in which the detection of the shot is the fundamental task. After the video is segmented into shots, extraction of key frames allows a suitable representation of the whole shot. Feature extraction is crucial processing step in the classification, video indexing and retrieval system. Frame features such as color, motion, texture, edges are extracted from the key frames. A baseball highlight contains certain types of scene shots and these shots follow a particular transition pattern. The shots are classified as close-up, out-field, base and audience. I first try to identify the type of the shot using low level features extracted from the key frames of each shot. For the identification of the highlight I use the hidden Markov model using the transition pattern of the shots in time domain. Experimental results suggest that with reasonable accuracy highlights can be extracted from the video.

Personal file retrieval – the task of locating and opening files on a computer – is a common task for all computer users. A range of interfaces are available to assist users in retrieving files, such as navigation within a file browser, search interfaces and recent items lists. This thesis examines two broad goals in file retrieval: understanding current file retrieval behaviour, and improving file retrieval by designing improved user interfaces. A thorough understanding of current file retrieval behaviour is important to the design of any improved retrieval tools, however there has been surprisingly little research about the ways in which users interact with common file retrieval tools. To address this, this thesis describes a longitudinal field study that logs participants' file retrieval behaviour across a range of methods, using a specially developed logging tool called FileMonitor. Results confirm findings from previous research that search is used as a method of last resort, while providing new results characterising file retrieval. These include analyses of revisitation behaviour, file browser window reuse, and interactions between retrieval methods, as well as detailed characterisations of the use of navigation and search. Knowledge gained from this study assists in the design of three improvements to file navigation: Icon Highlights, Search Directed Navigation and Hover Menus. Icon Highlights highlight items that are considered the most likely to be accessed next. These highlights are determined using a new algorithm, AccessRank, which is designed to produce a set of results that is both accurate and stable over time. Search Directed Navigation highlights items that match, or contain items that match, a filename search query, allowing users to rehearse the mechanisms for expert performance in order to aid future retrievals, and providing greater context than the results of a traditional search interface. Hover Menus appear when hovering the mouse cursor above a folder, and provide shortcuts to highly ranked files and folders located at any depth within the folder. This allows users to reduce navigation times by skipping levels of the file hierarchy. These interfaces are evaluated in lab and field studies, allowing for both precise analysis of their relative strengths and weaknesses, while also providing a high degree of external validity. Results of the lab study show that all three techniques reduce retrieval times and are subjectively preferred by participants. For the field study, fully functional versions of Icon Highlights and Search Directed Navigation are implemented as part of Finder Highlights, a plugin to OS X's file manager. Results indicate that Icon Highlights significantly reduce file retrieval times, and that Search Directed Navigation was useful to those who used it, but faces barriers to adoption. Key contributions of this thesis include a review of previous literature on file management, a thorough characterisation of file retrieval behaviour, improved algorithms for predicting user behaviour and three improved interfaces for file retrieval. This research has the potential to improve a tedious activity that users perform many times a day, while also providing generalisable algorithms and interface concepts that are applicable to a wide range of interfaces beyond file management.

The chosen exihibitions in this study are Highlights. Famous and forgotten Art Treasures from Nationalmuseum from 2014 and the earlier one from 1941 My best artwork which is chosen artworks from private collectors in Stockholm. It is a compare of the two exhibitions about artists and their artworks. Even a discussion of what a artwork is if it is called masterpeice and the importance of a curator at the museum has in the situation of organize an exhibition. Besides that the study discuss two private collections in the first decade of 1900.

The main goal of this work is to prepare proposal for new subsegment of information system, that reports on activity of automas. The main focus is on selection events, that have meaning for users, propose the methodology for automatic detection of selected events and prepare implementation instuctions for frontend pragrammers.

Three dimensional (3D) shape reconstruction that aims to reconstruct 3D surface of objects using acquired images, is one of the main problems in computer vision. There are many applications of 3D shape reconstruction, from satellite imaging to material sciences, considering a continent on earth or microscopic surface properties of a material. One of these applications is the automated firearm identification that is an old, yet an unsolved problem in forensic science. Firearm evidence matching algorithms rely on the fact that a firearm creates characteristic marks on surfaces of the bullets and the cartridge cases. These marks should be digitized unaffected from different surface material properties of evidences. Accuracy of 3D shape is one of the most important parameters affecting the overall identification performance. A very high resolution, accurate 3D data have to be reconstructed in the order of minutes. Photometric stereo (PS) method is capable of reconstructing high resolution surfaces in a fast manner. But, the metallic material and the surface topology of the firearm evidences generate highlights and shadows on their images that does not comply with the assumptions of conventional PS. In the scope of this work, it is intended to design an accurate, fast and robust 3D shape reconstruction scheme using PS considering highlights and shadows. These new PS procedures to be developed here should not be limited only to the ballistic evidences but they also could be used for a wider range of objects reflection properties and texture. For this purpose, masked PS methods which are quite fast when compared to other approaches, were classified and implemented. Simple additional masking methods are also proposed. A novel weighted PS method, using weighted least square estimation, is presented to eliminate false edges created by the masks. Concurrently, the calibration processes and the illumination configuration were improved. The disturbances due to close light sources were removed by image calibrations. From experimental tests to simulate the light positioning problem, it is concluded that the double zenith illumination configuration have better performance than the optimal single zenith illumination configuration, when the highlights and the shadows are considered. Double zenith illumination configuration results were further improved by the weighted normal PS with a small additional computation cost. All the implemented methods were tested firstly on the controlled environment using synthetic images. Later the same tests were conducted on real objects with varying characteristics as well as the firearm evidences.

Environments with people are complex, with many activities and events that need to be represented and explained. The goal of scene understanding is to either determine what objects and people are doing in such complex and dynamic environments, or to know the overall happenings, such as the highlights of the scene. The context within which the activities and events unfold provides key insights that cannot be derived by studying the activities and events alone. \emph{In this thesis, we show that this rich contextual information can be successfully leveraged, along with the video data, to support dynamic scene understanding}. We categorize and study four different types of contextual cues: (1) spatio-temporal context, (2) egocentric context, (3) geographic context, and (4) environmental context, and show that they improve dynamic scene understanding tasks across several different application domains. We start by presenting data-driven techniques to enrich spatio-temporal context by augmenting Bag-of-Words models with temporal, local and global causality information and show that this improves activity recognition, anomaly detection and scene assessment from videos. Next, we leverage the egocentric context derived from sensor data captured from first-person point-of-view devices to perform field-of-view localization in order to understand the user's focus of attention. We demonstrate single and multi-user field-of-view localization in both indoor and outdoor environments with applications in augmented reality, event understanding and studying social interactions. Next, we look at how geographic context can be leveraged to make challenging ``in-the-wild" object recognition tasks more tractable using the problem of food recognition in restaurants as a case-study. Finally, we study the environmental context obtained from dynamic scenes such as sporting events, which take place in responsive environments such as stadiums and gymnasiums, and show that it can be successfully used to address the challenging task of automatically generating basketball highlights. We perform comprehensive user-studies on 25 full-length NCAA games and demonstrate the effectiveness of environmental context in producing highlights that are comparable to the highlights produced by ESPN.

Title: Financial comparison of Czech and Slovak ski resorts Objectives: The aim of this thesis is to compare financial situation of selected Czech and Slovak ski resorts and on the basis of financial analysis to assess the financial health of these resorts. Methods: In this thesis, I used the method of vertical and horizontal analysis of the sources of financing of selected companies, evaluation of compliance with the golden rule of balance sheet, and using selected ratios refers the thesis about the financial situation of the company. Results: Data obtained from research helped me to identify aspects of the financial environment in which selected companies have drawbacks. In conclusion it is summarized individual measures serving to improve the financial health of companies. Keywords: financial analysis, winter sports, financial highlihts, financing of ski center ski

Η διπλωματική εκπονήθηκε με σκοπό τη δημιουργία προγράμματος που θα έχει ως δεδομένο το συμπιεσμένο βίντεο ενός ποδοσφαιρικού αγώνα και θα επιστρέφει σε μορφή βίντεο τα κυριότερα στιγμιότυπα. Ακόμα υλοποιήθηκαν διάφορες εκδοχές εντοπισμού των βασικών στοιχείων ενός ποδοσφαιρικού αγώνα, όπως οι γραμμές του αγωνιστικού χώρου, η θέση της μπάλας στο γήπεδο ο αριθμός και η πυκνότητα των παιχτών εντός του αγωνιστικού χώρου και η ύπαρξη ή μη του τέρματος εντός ενός frame. Πέραν του εντοπισμού της θέσης της μπάλας, δημιουργήθηκαν και προγράμματα για ball tracking (παρακολούθηση τροχιάς της μπάλας) και σε ειδικές περιπτώσεις, όπως για παράδειγμα σε βίντεο που περιέχει παίχτες με άσπρες φανέλες. Το πρόγραμμα εξαγωγής των φάσεων παίρνει τα παραπάνω στοιχεία που έχουν εντοπιστεί, τα επεξεργάζεται και με κατάλληλο συνδυασμό τους εξάγει συμπέρασμα για το πόσο σημαντικό είναι το εκάστοτε στιγμιότυπο. Πρόκειται, στην ουσία, για ένα είδος αυτόματου μοντάζ που βασίζεται στις τεχνικές της επεξεργασίας εικόνας. / Τhe project in question was accomplished to create an algorithm based on the compressed video of a football match and it will be able to replay the most important events of the match. In addition, several versions of locating the basic elements of a football match were produced, such as the lining of the pitch, the position of the ball on the pitch, the number of players and the players’ pixel density as well as the potential existence of the goalpost within a particular frame. Apart from the identification of the ball's position, additional algorithms of ball tracking were created for special cases, such as videos with players wearing white T-shirts. The highlight detection method relies on the appropriate combination of the previously stated elements (i.e. pitch lining, number of players etc.) and it can finally draw a conclusion on the significance of every moment of the match. In summary, this algorithm can be characterized as "automatic montage", based on the premises of image processing.

Recent research approaches in semantics based video content analysis require shot boundary detection as the first step to divide video sequences into sections. Furthermore, with the advances in networking and computing capability, efficient retrieval of multimedia data has become an important issue. Content-based retrieval technologies have been widely implemented to protect intellectual property rights (IPR). In addition, automatic recognition of highlights from videos is a fundamental and challenging problem for content-based indexing and retrieval applications. In this thesis, a paradigm is proposed to segment, retrieve and interpret digital videos. Five algorithms are presented to solve the video segmentation task. Firstly, a simple shot cut detection algorithm is designed for real-time implementation. Secondly, a systematic method is proposed for shot detection using content-based rules and FSM (finite state machine). Thirdly, the shot detection is implemented using local and global indicators. Fourthly, a context awareness approach is proposed to detect shot boundaries. Fifthly, a fuzzy logic method is implemented for shot detection. Furthermore, a novel analysis approach is presented for the detection of video copies. It is robust to complicated distortions and capable of locating the copy of segments inside original videos. Then, iv objects and events are extracted from MPEG Sequences for Video Highlights Indexing and Retrieval. Finally, a human fighting detection algorithm is proposed for movie annotation.