Learned Multi-Patch Similarity

Estimating a depth map from multiple views of a scene is a fundamental task in computer vision. As soon as more than two viewpoints are available, one faces the very basic question how to measure similarity across >2 image patches. Surprisingly, no direct solution exists, instead it is common to fall back to more or less robust averaging of two-view similarities. Encouraged by the success of machine learning, and in particular convolutional neural networks, we propose to learn a matching function which directly maps multiple image patches to a scalar similarity score. Experiments on several multi-view datasets demonstrate that this approach has advantages over methods based on pairwise patch similarity.Comment: 10 pages, 7 figures, Accepted at ICCV 201

Progressive Structure from Motion

Structure from Motion or the sparse 3D reconstruction out of individual photos is a long studied topic in computer vision. Yet none of the existing reconstruction pipelines fully addresses a progressive scenario where images are only getting available during the reconstruction process and intermediate results are delivered to the user. Incremental pipelines are capable of growing a 3D model but often get stuck in local minima due to wrong (binding) decisions taken based on incomplete information. Global pipelines on the other hand need the access to the complete viewgraph and are not capable of delivering intermediate results. In this paper we propose a new reconstruction pipeline working in a progressive manner rather than in a batch processing scheme. The pipeline is able to recover from failed reconstructions in early stages, avoids to take binding decisions, delivers a progressive output and yet maintains the capabilities of existing pipelines. We demonstrate and evaluate our method on diverse challenging public and dedicated datasets including those with highly symmetric structures and compare to the state of the art.Comment: Accepted to ECCV 201

Dynamic behaviour of brain and surrogate materials under ballistic impact

In the last several decades the number of the fatalities related to criminally inflicted cranial gunshot wounds has increased (Aarabi et al.; Jena et al., 2014; Mota et al., 2003). Back-spattered bloodstain patterns are often important in investigations of cranial gunshot fatalities, particularly when there is a doubt whether the death is suicide or homicide. Back-spatter is the projection of blood and tissue back toward the firearm. However, the mechanism of creation of the backspatter is not understood well. There are several hypotheses, which describe the formation of the backspatter. However, as it is difficult to study the internal mechanics of formation of the backspatter in animal experiments as the head is opaque and sample properties vary from animal to animal. Performing ballistic experiments on human cadavers is rarely not possible for ethical reasons. An alternative is to build a realistic physical 3D model of the human head, which can be used for reconstruction of crime scenes and BPA training purposes. This requires a simulant material for each layer of the human head. In order to build a realistic model of human head, it is necessary to understand the effect of the each layer of the human head to the generation of the back-spatter. Simulant materials offer the possibility of safe, well‐controlled experiments. Suitable simulants must be biologically inert, be stable over some reasonable shelf‐life, and respond to ballistic penetration in the same way as the responding human tissues. Traditionally 10-20% (w/w) gelatine have been used as a simulant for human soft tissues in ballistic experiments. However, 10-20% of gelatine has never been validated as a brain simulant. Moreover, due to the viscoelastic nature of the brain it is not possible to find the exact mechanical properties of the brain at ballistic strain rates. Therefore, in this study several experiments were designed to obtain qualitative and quantitative data using high speed cameras to compare different concentrations of gelatine and new composite material with the bovine and ovine brains. Factors such as the form of the fragmentation, velocity of the ejected material, expansion rate, stopping distance, absorption of kinetic energy and effect of the suction as well as ejection of the air from the wound cavity and its involvement in the generation of the backspatter have been investigated. Furthermore, in this study a new composite material has been developed, which is able to create more realistic form of the fragmentation and expansion rate compared to the all different percentage of the gelatine. The results of this study suggested that none of the concentrations the gelatine used in this study were capable of recreating the form of the damage to the one observed from bovine and ovine brain. The elastic response of the brain tissue is much lower that observed in gelatine samples. None of the simulants reproduced the stopping distance or form of the damage seen in bovine brain. Suction and ejection of the air as a result of creation of the temporary cavity has a direct relation to the elasticity of the material. For example, by reducing the percentage of the gelatine the velocity of the air drawn into the cavity increases however, the reverse scenario can be seen for the ejection of the air. This study showed that elastic response of the brain tissue was not enough to eject the brain and biological materials out of the cranium. However, the intracranial pressure raises as the projectile passes through the head. This pressure has the potential of ejecting the brain and biological material backward and create back-spatter. Finally, the results of this study suggested that for each specific type of experiment, a unique simulant must be designed to meet the requirements for that particular experiment

Bank accounts for students in the Czech republic

Import 10/08/2007Prezenční152 - Katedra podnikohospodářsk

Incremental Structure from Motion for Large Ordered and Unordered Sets of Images

Structure from Motion (SfM) computation from large unordered image sets is dominated by image feature matching. This thesis proposes avoiding exhaustive pairwise image matching by sampling pairs of images and estimating visual overlap using the detected occurrences of visual words. Although this technique alone leads to a significant speedup of SfM computation, the efficiency of the reconstruction from redundant image sets, e.g. community image sets of cities with landmarks, can be further improved by using the proposed image set reduction technique which performs selection of a small subset from the set of input images by computing the approximate minimum connected dominating set of a graph expressing image similarity. The efficiency of SfM computation can be also disrupted by spending too much time in a few difficult matching problems instead of exploring other easier options first. We propose using a priority queue for interleaving different SfM tasks as this facilitates obtaining reasonable reconstructions in limited time. The priorities of the individual tasks are set according to the estimated visual overlap again but they are also influenced by the history of the computation

Construction of the Factory On a Green Feld In Terms of Information Systems

Import 22/07/2015V předložené bakalářské práci je zpracována analýza výstavby nové výrobní haly společnosti DaughterCompany z pohledu informačních technologií a jejich implementaci v korporátním prostředí. Cílem práce je analýza a návrh jednotlivých implementačních kroků pro reálný projekt, který se bude realizovat v následujících letech.This bachelor thesis covers analysis of a new production center for company DaughterCompany from the perspective of information technologies and its implementation in the corporate environment. The objective of this work is the analysis and design of particular implementation steps for a real project, which is pending implementation in the coming years.Prezenční545 - Institut ekonomiky a systémů řízenívýborn

Sales Analysis

Import 31/08/2009Prezenční152 - Katedra podnikohospodářskádobř