3D Mesh Simplification. A survey of algorithms and CAD model simplification tests

Simplification of highly detailed CAD models is an important step when CAD models are visualized or by other means utilized in augmented reality applications. Without simplification, CAD models may cause severe processing and storage is- sues especially in mobile devices. In addition, simplified models may have other advantages like better visual clarity or improved reliability when used for visual pose tracking. The geometry of CAD models is invariably presented in form of a 3D mesh. In this paper, we survey mesh simplification algorithms in general and focus especially to algorithms that can be used to simplify CAD models. We test some commonly known algorithms with real world CAD data and characterize some new CAD related simplification algorithms that have not been surveyed in previous mesh simplification reviews.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

3D-tulostettu tuuliturbiinin vaihteen pienoismalli

Työn aiheena on vaihteen pienoismallin suunnittelu ja toteutus 3d-tulostusta hyväksi käyttäen. Pienoismalli tehdään Moventas Gears Oy:n suunnittelemasta tuuliturbiinin vaihteesta. Vaihteen pienentämisestä johtuen malliin on suunniteltava uudet laakeripesät ja hammaspyörät. 3D-tulostuksen ja pienoismallin pienen koon ansiosta vaihdetta voidaan yksinkertaistaa suuresti ja näin vähentää tulostettavien osien määrää. Lisäksi työssä selvitetään, mitä ongelmia 3D-tulostus tuo valmistukseen ja suunnitteluun. Työn kirjallisessa osassa selvennetään planeettavaihteen toimintaa yleisesti sekä esitellään Exceed Series 3+ vaihdetta. Lisäksi kerrotaan 3D-tulostuksesta, sen periaatteesta, erilaisista tulostusmenetelmistä, tulostinlaitteesta ja mahdollisista ongelmista tulostuksessa. Kokeellinen osa koostuu pienoismallin suunnittelusta ja valmistuksesta. Valmistuksessa olleiden virheiden takia muutama osa jouduttiin tulostamaan uudelleen. Muutamia osia jouduttiin myös hieman jälkikäsittelemään tulostuksen jälkeen, jotta malli saatiin kasattua. Ongelmakohdaksi muodostui tulostimen ohjelmisto ja tulostustiedostot. Tulostusprosessi sujui kuitenkin hyvin. Lopputuloksena saatiin toimiva pienoismalli. 3D-tulostus toimii hyvin monimutkaisten kappaleiden tulostuksessa. Tulostuksen hinta nousi kuitenkin varsin korkeaksi. Tulostuslaitteistosta riippuen tulostuksen voisi mahdollisesti suorittaa myös halvemmallakin.

Näkökulmia 3D-tulostuksen opetukseen ja koulutukseen

Additive manufacturing, or 3D printing, is globally one of most interesting area in developing of manufacturing technologies. This technology is suitable for fabrication off industrial products and it interests actors in fields of computer sciences, economics, medical sciences and design&arts. Additive manufacturing is often referred as third industrial revolution: first revolution was invention of steam engines in 18th century and second was industrial revolution started by Henry Ford in 1920s. Companies should be able to test suitability of their products for additive manufacturing and 3D printing but also how much better products could be when products are totally re-designed so that all potential of this new technology can be utilized. This is where education has its importance; new generations who enter working life should be educated to know of additive manufacturing and 3D printing, its advantages but also of it limits. There has to be also possibility to educate industry and people already working there, so that industrial implementation could be done successfully. This is especially very valid for Finland. Education is strongly needed so that Finnish industry can maintain its competence in global markets. Role of education is extremely important when a new technology is industrially implemented. Additive manufacturing and 3D printing offers freedom to design new products, production and generally ways of doing things. Development, planning and execution of education for additive manufacturing and 3D printing is challenging as this area develops very fast. New innovations are coming almost every month. Planning of education for additive manufacturing and 3D printing requires collection pieces of data from various of sources. Additive manufacturing and 3D printing industry and its development has to be followed frequently, and material for additive manufacturing and 3D printing has to be renewed frequently.

Rigid body dynamics and Kalman filtering

X-ray computed log tomography has always been applied for qualitative reconstructions. In most cases, a series of consecutive slices of the timber are scanned to estimate the 3D image reconstruction of the entire log. However, the unexpected movement of the timber under study influences the quality of image reconstruction since the position and orientation of some scanned slices can be incorrectly estimated. In addition, the reconstruction time remains a significant challenge for practical applications. The present study investigates the possibility to employ modern physics engines for the problem of estimating the position of a moving rigid body and its scanned slices which are subject to X-ray computed tomography. The current work includes implementations of the extended Kalman filter and an algebraic reconstruction method for fan-bean computer tomography. In addition, modern techniques such as NVidia PhysX and CUDA are used in current study. As the result, it is numerically shown that it is possible to apply the extended Kalman filter together with a real-time physics engine, known as PhysX, in order to determine the position of a moving object. It is shown that the position of the rigid body can be determined based only on reconstructions of its slices. However, the simulation of the body movement sometimes is subject to an error during Kalman filter employment as PhysX is not always able to continue simulating the movement properly because of incorrect state estimation.

Development of 3D super-resolution tomographic STED microscopy and its application to studies on bone resorption

In this doctoral thesis, a tomographic STED microscopy technique for 3D super-resolution imaging was developed and utilized to observebone remodeling processes. To improve upon existing methods, wehave used a tomographic approach using a commercially available stimulated emission depletion (STED) microscope. A certain region of interest (ROI) was observed at two oblique angles: one at a standard inverted configuration from below (bottom view) and another from the side (side view) via a micro-mirror positioned close to the ROI. The two viewing angles were reconstructed into a final tomogram. The technique, named as tomographic STED microscopy, was able to achieve an axial resolution of approximately 70 nm on microtubule structures in a fixed biological specimen. High resolution imaging of osteoclasts (OCs) that are actively resorbing bone was achieved by creating an optically transparent coating on a microscope coverglass that imitates a fractured bone surface. 2D super-resolution STED microscopy on the bone layer showed approximately 60 nm of lateral resolution on a resorption associated organelle allowing these structures to be imaged with super-resolution microscopy for the first time. The developed tomographic STED microscopy technique was further applied to study resorption mechanisms of OCs cultured on the bone coating. The technique revealed actin cytoskeleton with specific structures, comet-tails, some of which were facing upwards and some others were facing downwards. This, in our opinion, indicated that during bone resorption, an involvement of the actin cytoskeleton in vesicular exocytosis and endocytosis is present. The application of tomographic STED microscopy in bone biology demonstrated that 3D super-resolution techniques can provide new insights into biological 3D nano-structures that are beyond the diffraction-limit when the optical constraints of super-resolution imaging are carefully taken into account.

Pituusleikkureiden 3D-suunnittelun kehittäminen

Tämä diplomityö tehtiin Valmet Technologies Oy:n Järvenpään toimipisteelle. Työn tavoitteena oli tutkia miten pituusleikkureiden 3D-suunnittelua voidaan tehostaa hyödyntämällä uuden 3D-CAD -järjestelmän ominaisuuksia optimaalisesti. Työ koostuu teoriaosuudesta, haastattelututkimuksesta sekä käytännön osuudesta. Teoriaosuudessa perehdytään pituusleikkurin toimintaan ja rakenteeseen, 3D-suunnittelun teoriaan sekä CATIA-järjestelmään. Teoriaosuudessa etsitään myös uusia näkökulmia 3D-suunnitteluun. Haastattelututkimuksessa kartoitetaan nykyinen suunnitteluprosessi, suunnittelun kehitettäviä kohteita, sekä käytössä olevia suunnittelumenetelmiä, jotka ovat todettu toimiviksi. Haastattelututkimuksessa haastatellaan Valmet Technologies Oy:n Järvenpään toimipisteessä työskenteleviä pituusleikkureiden pääsuunnittelijoita sekä heidän esimiehiään. Lisäksi erillisten haastattelujen avulla kerätään kokemuksia CATIA V6 -ohjelmiston käytöstä sekä suunnitteluohjelmiston vaihtumisesta. Käytännön osuuden tavoitteena on arvioida pituusleikkurin parametroitujen mallirakenteiden siirtämiseen sekä korjauksiin kuluvia aikamääriä kyseisiin toimenpiteisiin tarvittavien resurssien määrittämiseksi. Käytännön osuudessa siirretään kaksi Valmet OptiWin Drum Compact -pituusleikkurin parametroitua osakokonaisuutta uuteen CAD-järjestelmään ja niille suoritetaan tarvittavat korjaustoimenpiteet Tutkimuksen tulosten perusteella yhteisen mallinnusmetodologian puuttuminen on merkittävin kehityskohde suunnittelun kehittämisessä. Lopuksi luotiin kehitysehdotukset sekä implementointisuunnitelma, joiden avulla pituusleikkureiden 3D-suunnittelua voidaan kehittää ja CATIA V6 -ohjelmisto voidaan ottaa käyttöön tehokkaasti.

Näin opetan lisäävää valmistusta ja 3D-tulostusta: Pohdintoja uuden teknologian opetuksesta ja koulutuksesta

Additive manufacturing (shortened as AM), or more commonly 3D printing, consists of wide variety of different modern manufacturing technologies. AM is based on direct printing of a digital 3D model to a final product which is fabricated adding material layer by layer. This is from where term additive manufacturing has its origin. It is not only material what is added, but it is also value, properties etc. which are added. AM enables production of different and even better products compared to conventional manufacturing technologies. An estimation of potential of additive manufacturing can be gathered by considering the potential of laser cutting, which is one of the most widely used modern manufacturing technologies. This technique has been used over 40 years, and whole market around this technology is at the moment c. four billion euros and yearly growth is around 10 %. One factor affecting this success of laser cutting is that laser cutting enables radical improvements to products made of flat sheet. AM and 3D printing will do the same for three dimensional parts. Laser devices, which are at the moment used in 3D printing, are globally at the moment only around 1% of all laser devices used in any fabrication technology, so even with a cautious estimate the potential growth of at least 100 % is coming in next few years. Role of education is very important, when this kind of modern technology is industrially implemented. When both generation entering to work life and also generation who has been a while in work life understands new technology, its potential and limitations, this is the point when also product design can be rethought Potential of product design is driving force for wide use of additive manufacturing and 3D printing. Utilization of additive manufacturing and 3D printing is also opportunity for Finland and Finnish industry. This technology can save Finnish manufacturing industry. This technique has stron potential, as Finland has traditionally strong industrial know-how and good ICT knowledge.