Free-Shape Polygonal Object Localization

Polygonal objects are prevalent in man-made scenes. Early approaches to detecting them relied mainly on geometry while subsequent ones also incorporated appearance-based cues. It has recently been shown that this could be done fast by searching for cycles in graphs of line-fragments, provided that the cycle scoring function can be expressed as additive terms attached to individual fragments. In this paper, we propose an approach that eliminates this restriction. Given a weighted line-fragment graph, we use its cyclomatic number to partition the graph into managebly-sized sub-graphs that preserve nodes and edges with a high weight and are most likely to contain object contours. Object contours are then detected as maximally scoring elementary circuits enumerated in each sub-graph. Our approach can be used with any cycle scoring function and multiple candidates that share line fragments can be found. This is unlike in other approaches that rely on a greedy approach to finding candidates. We demonstrate that our approach significantly outperforms the state-of-the-art for the detection of building rooftops in aerial images and polygonal object categories from ImageNet

The what and where in visual object recognition

Sinds kort zijn de technieken om objecten in beelden te herkennen nauwkeurig genoeg om te gebruiken in zoektaken, zoals bijvoorbeeld in Google Image search. Toch blijft het voor computers lastig om objecten te herkennen in een foto. Jasper Uijlings deed onderzoek naar het zogenaamde Bag-of-Words-model en leverde een bijdrage aan de versnelling van het algoritme. Bij het Bag-of-Words- model wordt het beeld opgedeeld in kleine stukjes. Ieder stukje wordt toegekend aan categorieën zoals hoekig, strepig, of egaal blauw. Vervolgens wordt aan het aantal stukjes hoekig en strepig bepaald of er bijvoorbeeld een koe in het plaatje staat. Wat vreemd is aan deze Bag-of-Words-representatie is dat de locatie van een object volledig wordt genegeerd. Uijlings concludeert dat het goed zou zijn om de objectlocatie weer terug te brengen. Daartoe ontwikkelde hij een methode die de objectlocatie op een efficiënte manier kan representeren. Hiermee is het mogelijk om meerdere objecten in een beeld te identificeren, in plaats van alleen individuele beelden

What is the spatial extent of an object?

This paper discusses the question: Can we improve the recognition of objects by using their spatial context? We start from Bag-of-Words models and use the Pascal 2007 dataset. We use the rough object bounding boxes that come with this dataset to investigate the fundamental gain context can bring. Our main contributions are: (I) The result of Zhang et al. in CVPR07 that context is superfluous derived from the Pascal 2005 data set of 4 classes does not generalize to this dataset. For our larger and more realistic dataset context is important indeed. (II) Using the rough bounding box to limit or extend the scope of an object during both training and testing, we find that the spatial extent of an object is determined by its category: (a) well-defined, rigid objects have the object itself as the preferred spatial extent. (b) Non-rigid objects have an unbounded spatial extent : all spatial extents produce equally good results. (c) Objects primarily categorised based on their function have the whole image as their spatial extent. Finally, (III) using the rough bounding box to treat object and context separately, we find that the upper bound of improvement is 26% (12% absolute) in terms of mean average precision, and this bound is likely to be higher if the localisation is done using segmentation. It is concluded that object localisation, if done sufficiently precise, helps considerably in the recognition of objects for the Pascal 2007 dataset

Aircrafts Maintenance Efficiency according the Hangars Workplace Organization

Import 31/08/2009ANOTACE BAKALÁŘSKÉ PRÁCE Jurák P. Efektivnost provádění údržby letecké techniky v závislosti na uspořádání provozní plochy hangáru. Ostrava: Institut dopravy, Fakulta strojní VŠB – Technické universita Ostrava, 2009, 60 stran, Bakalářská práce, vedoucí Kolarczyk P. Podkladem k napsání bakalářské práce byl požadavek na návrh takového řešení údržby letadel, které by umožnilo zvýšit efektivitu jejího provádění v závislosti na uspořádání prostor hangáru. Celkové řešení modelu uspořádání hangáru je ovlivňováno potřebnou velikostí pracovní plochy, nutným technickým vybavením pro údržbu, servisovanou LT a časovou náročností její údržby. Analýzou výše zmíněných prvků jsem dospěl k závěru, jakým způsobem uspořádat servisní linky a následně je umístit na pracovní ploše. Informace zjištěné analýzou přímo ve stávajících procesech údržby, také pomohly navrhnout postup při zavádění nových servisních linek ve vztahu k budoucímu předpokládanému vývoji firmy JOB AIR – CEAM a.s. V závěru této práce předkládám zhodnocení přínosu navrhovaného řešení na efektivitu prováděné údržby.ANOTATION OF THESIS Jurák P. Aircraft´s Maintenance Efficiency according the Hangar´s Workplace Organization. Ostrava: Institute transport Faculty of Mechanical Engineering VŠB - Technical University of Ostrava, 2009, 60 pages, Bachelor’s thesis, supervisor Kolarczyk P. This Bachelor Thesis was written to suggest an effective aircraft maintenance, depending on hangar layout. This hangar layout demands a certain size of the working place, technical equipment for the maintenance, serviced aeronautical technics and time heftiness of the maintenance. After analysing above mentioned requirements I came to a solution, how to order service line and further how to place them on the working space. Reached information from the process of maintenance helped to put forward a procedure of implementing of the service lines relating to the supposed future developement of the JOB AIR – CEAM a.s. company. At the end of this thesis I offer an evaluation of the benefit reached by the suggested solution of an effective maintenace.Neuvedenovýborn