GraphMatch: Efficient Large-Scale Graph Construction for Structure from Motion

We present GraphMatch, an approximate yet efficient method for building the matching graph for large-scale structure-from-motion (SfM) pipelines. Unlike modern SfM pipelines that use vocabulary (Voc.) trees to quickly build the matching graph and avoid a costly brute-force search of matching image pairs, GraphMatch does not require an expensive offline pre-processing phase to construct a Voc. tree. Instead, GraphMatch leverages two priors that can predict which image pairs are likely to match, thereby making the matching process for SfM much more efficient. The first is a score computed from the distance between the Fisher vectors of any two images. The second prior is based on the graph distance between vertices in the underlying matching graph. GraphMatch combines these two priors into an iterative "sample-and-propagate" scheme similar to the PatchMatch algorithm. Its sampling stage uses Fisher similarity priors to guide the search for matching image pairs, while its propagation stage explores neighbors of matched pairs to find new ones with a high image similarity score. Our experiments show that GraphMatch finds the most image pairs as compared to competing, approximate methods while at the same time being the most efficient.Comment: Published at IEEE 3DV 201

Automatic Interpretation of Melanocytic Images in Confocal Laser Scanning Microscopy

The frequency of melanoma doubles every 20 years. The early detection of malignant changes augments the therapy success. Confocal laser scanning microscopy (CLSM) enables the noninvasive examination of skin tissue. To diminish the need for training and to improve diagnostic accuracy, computer-aided diagnostic systems are required. Two approaches are presented: a multiresolution analysis and an approach based on deep layer convolutional neural networks. For the diagnosis of the CLSM views, architectural structures such as micro-anatomic structures and cell nests are used as guidelines by the dermatologists. Features based on the wavelet transform enable an exploration of architectural structures at different spatial scales. The subjective diagnostic criteria are objectively reproduced. A tree-based machine-learning algorithm captures the decision structure explicitly and the decision steps are used as diagnostic rules. Deep layer neural networks require no a priori domain knowledge. They are capable of learning their own discriminatory features through the direct analysis of image data. However, deep layer neural networks require large amounts of processing power to learn. Therefore, modern neural network training is performed using graphics cards, which typically possess many hundreds of small, modestly powerful cores that calculate massively in parallel. Readers will learn how to apply multiresolution analysis and modern deep learning neural network techniques to medical image analysis problems

The visual preferences for forest regeneration and field afforestation : four case studies in Finland

The overall aim of this dissertation was to study the public's preferences for forest regeneration fellings and field afforestations, as well as to find out the relations of these preferences to landscape management instructions, to ecological healthiness, and to the contemporary theories for predicting landscape preferences. This dissertation includes four case studies in Finland, each based on the visualization of management options and surveys. Guidelines for improving the visual quality of forest regeneration and field afforestation are given based on the case studies. The results show that forest regeneration can be connected to positive images and memories when the regeneration area is small and some time has passed since the felling. Preferences may not depend only on the management alternative itself but also on the viewing distance, viewing point, and the scene in which the management options are implemented. The current Finnish forest landscape management guidelines as well as the ecological healthiness of the studied options are to a large extent compatible with the public's preferences. However, there are some discrepancies. For example, the landscape management instructions as well as ecological hypotheses suggest that the retention trees need to be left in groups, whereas people usually prefer individually located retention trees to those trees in groups. Information and psycho-evolutionary theories provide some possible explanations for people's preferences for forest regeneration and field afforestation, but the results cannot be consistently explained by these theories. The preferences of the different stakeholder groups were very similar. However, the preference ratings of the groups that make their living from forest - forest owners and forest professionals - slightly differed from those of the others. These results provide support for the assumptions that preferences are largely consistent at least within one nation, but that knowledge and a reference group may also influence preferences.Väitöskirjassa tutkittiin ihmisten maisemapreferenssejä (maisemallisia arvostuksia) metsänuudistamishakkuiden ja pellonmetsitysten suhteen sekä analysoitiin näiden preferenssien yhteyksiä maisemanhoito-ohjeisiin, vaihtoehtojen ekologiseen terveyteen ja preferenssejä ennustaviin teorioihin. Väitöskirja sisältää neljä tapaustutkimusta, jotka perustuvat hoitovaihtoehtojen visualisointiin ja kyselytutkimuksiin. Tapaustutkimusten pohjalta annetaan ohjeita siitä, kuinka uudistushakkuiden ja pellonmetsitysten visuaalista laatua voidaan parantaa. Väitöskirjan tulokset osoittavat, että uudistamishakkuut voivat herättää myös myönteisiä mielikuvia ja muistoja, jos uudistusala on pieni ja hakkuun välittömät jäljet ovat jo peittyneet. Preferensseihin vaikuttaa hoitovaihtoehdon lisäksi mm. katseluetäisyys, katselupiste ja ympäristö, jossa vaihtoehto on toteutettu. Eri viiteryhmien (metsäammattilaiset, pääkaupunkiseudun asukkaat, ympäristönsuojelijat, tutkimusalueiden matkailijat, paikalliset asukkaat sekä metsänomistajat) maisemapreferenssit olivat hyvin samankaltaisia. Kuitenkin ne ryhmät, jotka saavat ainakin osan elannostaan metsästä - metsänomistajat ja metsäammattilaiset - pitivät metsänhakkuita esittävistä kuvista hieman enemmän kuin muut ryhmät. Nämä tulokset tukevat oletusta, että maisemapreferenssit ovat laajalti yhteneväisiä ainakin yhden kansan tai kulttuurin keskuudessa, vaikka myös viiteryhmä saattaa vaikuttaa preferensseihin jonkin verran. Nykyiset metsämaisemanhoito-ohjeet ovat pitkälti samankaltaisia tässä väitöskirjassa havaittujen maisemapreferenssien kanssa. Myöskään tutkittujen vaihtoehtoisten hoitotapojen ekologisen paremmuuden ja niihin kohdistuvien maisemallisten arvostusten välillä ei ollut suurta ristiriitaa. Kuitenkin joitakin eroavaisuuksia oli; esimerkiksi sekä maisemanhoito-ohjeiden että ekologisten hypoteesien mukaan säästöpuut tulisi jättää ryhmiin, kun taas ihmiset pitivät eniten yksittäin jätetyistä puista. Informaatiomalli ja psyko-evolutionaarinen teoria tarjoavat mahdollisia selityksiä uudistushakkuisiin ja pellonmetsitykseen kohdistuville preferensseille, vaikkakaan tutkimuksen tuloksia ei voida täysin selittää näillä teorioilla