Gait Recognition from Motion Capture Data

Gait recognition from motion capture data, as a pattern classification discipline, can be improved by the use of machine learning. This paper contributes to the state-of-the-art with a statistical approach for extracting robust gait features directly from raw data by a modification of Linear Discriminant Analysis with Maximum Margin Criterion. Experiments on the CMU MoCap database show that the suggested method outperforms thirteen relevant methods based on geometric features and a method to learn the features by a combination of Principal Component Analysis and Linear Discriminant Analysis. The methods are evaluated in terms of the distribution of biometric templates in respective feature spaces expressed in a number of class separability coefficients and classification metrics. Results also indicate a high portability of learned features, that means, we can learn what aspects of walk people generally differ in and extract those as general gait features. Recognizing people without needing group-specific features is convenient as particular people might not always provide annotated learning data. As a contribution to reproducible research, our evaluation framework and database have been made publicly available. This research makes motion capture technology directly applicable for human recognition.Comment: Preprint. Full paper accepted at the ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), special issue on Representation, Analysis and Recognition of 3D Humans. 18 pages. arXiv admin note: substantial text overlap with arXiv:1701.00995, arXiv:1609.04392, arXiv:1609.0693

You Are How You Walk: Uncooperative MoCap Gait Identification for Video Surveillance with Incomplete and Noisy Data

This work offers a design of a video surveillance system based on a soft biometric -- gait identification from MoCap data. The main focus is on two substantial issues of the video surveillance scenario: (1) the walkers do not cooperate in providing learning data to establish their identities and (2) the data are often noisy or incomplete. We show that only a few examples of human gait cycles are required to learn a projection of raw MoCap data onto a low-dimensional sub-space where the identities are well separable. Latent features learned by Maximum Margin Criterion (MMC) method discriminate better than any collection of geometric features. The MMC method is also highly robust to noisy data and works properly even with only a fraction of joints tracked. The overall workflow of the design is directly applicable for a day-to-day operation based on the available MoCap technology and algorithms for gait analysis. In the concept we introduce, a walker's identity is represented by a cluster of gait data collected at their incidents within the surveillance system: They are how they walk

Similarity Search for Mathematics: Masaryk University team at the NTCIR-10 Math Task

This paper describes and summarizes experiences of Masaryk University team MIRMU with the mathematical search performed for the NTCIR pilot Math Task. Our approach is the similarity search based on enhanced full text search utilizing attested state-of-the-art techniques and implementations. The variability of used Math Indexer and Searcher (MIaS) system in terms of the math query notation was tested by submitting multiple runs with four query notations provided. The analysis of the evaluation results shows that the system performs best using TeX queries that are translated to combined Presentation-Content MathML

Unified Design of Box Gripper Telescopes for Navette and SMC Storage Machines

Cílem této diplomové práce je jednotný konstrukční návrh teleskopů pro automatizované zakladače typu SMC a Navette. Práce se skládá z technické a výkresové dokumentace. První část technické dokumentace je zaměřena na kritickou rešerši využívaných konstrukčních řešení ve světě. Ve druhé části následuje vlastní konstrukční řešení včetně výpočtové fáze návrhu. V poslední části byla zhotovena toleranční analýza navrženého teleskopu. Ve výkresové části práce byly zhotoveny výkresy, sestavy a podsestav.The aim of this diploma thesis is unified design of box gripper telescopes for Navette and SMC storage machines. The work contains technical report and drawings documentation. The first part of technical report is aim to research of similar constructions used in the world. Followed by own construction solution, including needed calculation. At the final part of work was created a tolerance analysis of new telescope. The drawings documentation contains assembly and subassembly drawings.

Improving RRT for Automated Parking in Real-world Scenarios

Automated parking is a self-driving feature that has been in cars for several years. Parking assistants in currently sold cars fail to park in more complex real-world scenarios and require the driver to move the car to an expected starting position before the assistant is activated. We overcome these limitations by proposing a planning algorithm consisting of two stages: (1) a geometric planner for maneuvering inside the parking slot and (2) a Rapidly-exploring Random Trees (RRT)-based planner that finds a collision-free path from the initial position to the slot entry. Evaluation of computational experiments demonstrates that improvements over commonly used RRT extensions reduce the parking path cost by 21 % and reduce the computation time by 79.5 %. The suitability of the algorithm for real-world parking scenarios was verified in physical experiments with Porsche Cayenne.Comment: 19 pages, 14 figures, 2 table

Redakční systém odborného časopisu s podporou exportu do digitální knihovny

summary:Postup zpracování odborných, zejména matematických časopisů je založen na TeXu a navazujících technologiích. Vydavatel většinou články zpřístupňuje a paralelně publikuje i elektronicky. Vytváří optimalizovanou verzi pro webové šíření, verzi pro archivaci, případně i verzi optimalizovanou pro čtení na obrazovce. Článek popisuje navržený a implementovaný postup zpracování několika matematických časopisů deponujících svou produkci v České digitální matematické knihovně DML-CZ a následně v Evropské digitální matematické knihovně EuDML.summary:Production workflow of publishing scientific, especially mathematical journals is based on TeX and related technologies. Publisher usually prepare and make papers available electronically in a digital library, optimized for digital delivery and eventually for reading too. Paper describes designed and implemented production workflow of several mathematical journals that archive their production in the Czech Digital Mathematics Library DML-CZ, which is subsequently available in the European Digital Mathematics Library EuDML