Visuaalinen haku ja silmänliikkeet : tutkimuksia havaintokentästä

Artikkeli perustuu Helena Ojanpään väitöskirjaan Visual search and eye movements : Studies of perceptual span (HY 2006).

Unsupervised visual object categorization

The number of digital images has been increasing exponentially in the last few years. People have problems managing their image collections and finding a specific image. An automatic image categorization system could help them to manage images and find specific images. In this thesis, an unsupervised visual object categorization system was implemented to categorize a set of unknown images. The system is unsupervised, and hence, it does not need known images to train the system which needs to be manually obtained. Therefore, the number of possible categories and images can be huge. The system implemented in the thesis extracts local features from the images. These local features are used to build a codebook. The local features and the codebook are then used to generate a feature vector for an image. Images are categorized based on the feature vectors. The system is able to categorize any given set of images based on the visual appearance of the images. Images that have similar image regions are grouped together in the same category. Thus, for example, images which contain cars are assigned to the same cluster. The unsupervised visual object categorization system can be used in many situations, e.g., in an Internet search engine. The system can categorize images for a user, and the user can then easily find a specific type of image.

Bag-of-Features Approach to Unsupervised Visual Object Categorisation

The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.

A comparison of one- and two-compartment neighbourhoods in heuristic search with spatial forest management goals

Abstract

Coarse Global Visual Localization of a Mobile Robot

Localization, which is the ability of a mobile robot to estimate its position within its environment, is a key capability for autonomous operation of any mobile robot. This thesis presents a system for indoor coarse and global localization of a mobile robot based on visual information. The system is based on image matching and uses SIFT features as natural landmarks. Features extracted from training images arestored in a database for use in localization later. During localization an image of the scene is captured using the on-board camera of the robot, features are extracted from the image and the best match is searched from the database. Feature matching is done using the k-d tree algorithm. Experimental results showed that localization accuracy increases with the number of training features used in the training database, while, on the other hand, increasing number of features tended to have a negative impact on the computational time. For some parts of the environment the error rate was relatively high due to a strong correlation of features taken from those places across the environment.

Laivan hitsattujen runkorakenteiden ainettarikkomattoman tarkastuksen ohjauksen ja valvonnan kehittäminen

Laivan rungonvalmistuksen laadunvarmistuksessa käytetään viranomaisten valvomia NDT-tarkastuksia vaatimustenmukaisuuden varmistamiseksi. Yleisimmin käytettävät NDT-tarkastusmenetelmät laivanrakennuksessa ovat visuaali-, röntgen-, ultraääni-, magneettijauhe- ja tunkeumanestetarkastukset. Diplomityön tavoitteena oli kehittää laivan hitsattujen runkorakenteiden ainettarikkomattoman tarkastuksen ohjausta ja valvontaa Aker Finnyards:n Turun telakalla. Työn alussa selvitettiin NDT-tarkastuksen ohjauksen ja valvonnannykytila ja tunnistettiin kehityskohteita. Tutkimusmenetelminä käytettiin työnmittausta ja havainnointitutkimusta. Merkittävimmiksi kehityskohteiksi havaittiinyleinen epätietoisuus NDT-tarkastuksista laivan runkoprosessissa, selkeän NDT-tarkastusten ohjausjärjestelmän puuttuminen sekä puutteellinen valvonta. Kehityskohteiden tunnistamisen perusteella luotiin toimintamalli NDT-tarkastusten ohjauksen ja valvonnan kehittämiseksi. Toimintamallissa on kuvattuna NDT-tarkastusprosessin tekijät ja informaatiovirrat. Toimintamalli on tarvittaessa päivitettävissä.

Visual measurement of laser-arc hybrid welding

Tässä työssä raportoidaan hybridihitsauksesta otettujen suurnopeuskuvasarjojen automaattisen analyysijärjestelmän kehittäminen.Järjestelmän tarkoitus oli tuottaa tietoa, joka avustaisi analysoijaa arvioimaan kuvatun hitsausprosessin laatua. Tutkimus keskittyi valokaaren taajuuden säännöllisyyden ja lisäainepisaroiden lentosuuntien mittaamiseen. Valokaaria havaittiin kuvasarjoista sumean c-means-klusterointimenetelmän avullaja perättäisten valokaarien välistä aikaväliä käytettiin valokaaren taajuuden säännöllisyyden mittarina. Pisaroita paikannettiin menetelmällä, jossa yhdistyi pääkomponenttianalyysi ja tukivektoriluokitin. Kalman-suodinta käytettiin tuottamaan arvioita pisaroiden lentosuunnista ja nopeuksista. Lentosuunnanmääritysmenetelmä luokitteli pisarat niiden arvioitujen lentosuuntien perusteella. Järjestelmän kehittämiseen käytettävissä olleet kuvasarjat poikkesivat merkittävästi toisistaan kuvanlaadun ja pisaroiden ulkomuodon osalta, johtuen eroista kuvaus- ja hitsausprosesseissa. Analyysijärjestelmä kehitettiin toimimaan pienellä osajoukolla kuvasarjoja, joissa oli tietynlainen kuvaus- ja hitsausprosessi ja joiden kuvanlaatu ja pisaroiden ulkomuoto olivat samankaltaisia, mutta järjestelmää testattiin myös osajoukon ulkopuolisilla kuvasarjoilla. Testitulokset osoittivat, että lentosuunnanmääritystarkkuus oli kohtuullisen suuri osajoukonsisällä ja pieni muissa kuvasarjoissa. Valokaaren taajuuden säännöllisyyden määritys oli tarkka useammassa kuvasarjassa.

In Search of Corporate Renewal: How to Benefit from Corporate Venturing?

Despite the rapid change in today's business environment there are relatively few studies about corporate renewal. This study aims for its part at filling that research gap by studying the concepts of strategy, corporate renewal, innovation and corporate venturing. Its purpose is to enhance our understanding of how established companies operating in dynamic and global environment can benefit from their corporate venturing activities. The theoretical part approaches the research problem in corporate and venture levels. Firstly, it focuses on mapping the determinants of strategy and suggests using industry, location, resources, knowledge, structure and culture, market, technology and business model to assess the environment and using these determinants to optimize speed and magnitude of change.Secondly, it concludes that the choice of innovation strategy is dependent on the type and dimensions of innovation and suggests assessing market, technology, business model as well as novelty and complexity related to each of them for choosing an optimal context for developing innovations further. Thirdly, it directsattention on processes through which corporate renewal takes place. On corporate level these processes are identified as strategy formulation, strategy formation and strategy implementation. On the venture level the renewal processes are identified as learning, leveraging and nesting. The theoretical contribution of this study, the framework of strategic corporate venturing, joins corporate and venture level management issues together and concludes that strategy processes and linking processes are the mechanism through which continuous corporate renewaltakes place. The framework of strategic corporate venturing proposed by this study is a new way to illustrate the role of corporate venturing as a purposefullybuilt, different view of a company's business environment. The empirical part extended the framework by enhancing our understanding of the link between corporate renewal and corporate venturing in its real life environment in three Finnish companies: Metso, Nokia and TeliaSonera. Characterizing companies' environmentwith the determinants of strategy identified in this study provided a structured way to analyze their competitive position and renewal challenges that they arefacing. More importantly the case studies confirmed that a link between corporate renewal and corporate venturing exists and found out that the link is not as straight forward as indicated by the theory. Furthermore, the case studies enhanced the framework by indicating a sequence according to which the processes work. Firstly, the induced strategy processes strategy formulation and strategy implementation set the scene for corporate venturing context and management processes and leave strategy formation for the venture. Only after that can strategies formed by ventures come back to the corporate level - and if found viable in the corporate level be formalized through formulation and implementation. With the help of the framework of strategic corporate venturing the link between corporaterenewal and corporate venturing can be found and managed. The suggested response to the continuous need for change is continuous renewal i.e. institutionalizing corporate renewal in the strategy processes of the company. As far as benefiting from venturing is concerned the answer lies in deliberately managing venturing in a context different to the mainstream businesses and establishing efficientlinking processes to exploit the renewal potential of individual ventures.

Anther culture properties of oat x wild red oat progenies and a search for RAPD markers associated with anther culture ability

Selostus: Ponsiviljeltävyys ja siihen liittyvät geenimerkit peltokauran ja susikauran risteytysjälkeläisissä

Evolutionary computing in search-based software engineering

This master’s thesis aims to study and represent from literature how evolutionary algorithms are used to solve different search and optimisation problems in the area of software engineering. Evolutionary algorithms are methods, which imitate the natural evolution process. An artificial evolution process evaluates fitness of each individual, which are solution candidates. The next population of candidate solutions is formed by using the good properties of the current population by applying different mutation and crossover operations. Different kinds of evolutionary algorithm applications related to software engineering were searched in the literature. Applications were classified and represented. Also the necessary basics about evolutionary algorithms were presented. It was concluded, that majority of evolutionary algorithm applications related to software engineering were about software design or testing. For example, there were applications about classifying software production data, project scheduling, static task scheduling related to parallel computing, allocating modules to subsystems, N-version programming, test data generation and generating an integration test order. Many applications were experimental testing rather than ready for real production use. There were also some Computer Aided Software Engineering tools based on evolutionary algorithms.