An integrated system for human action recognition from video using hidden Markov model

In this paper, we present an integrated system for real-time automatic detection of human actions from video. The proposed approach uses the boundary of humans as the main feature for recognizing actions. Background subtraction is performed using Gaussian mixture model. Then, features are extracted from silhouettes and Vector Quantization is used to map features into symbols (bag of words approach). Finally, actions are detected using the Hidden Markov Model. The proposed system was validated using a newly collected real- world dataset. The obtained results show that the system is capable of achieving robust human detection, in both indoor and outdoor environments. Moreover, promising classification results were achieved when detecting two basic human actions: walking and sitting.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

A general history of the dichlamydeous plants :comprising complete descriptions of the different orders...the whole arranged according to the natural system /by George Don.

1831 v.1

A general history of the dichlamydeous plants :comprising complete descriptions of the different orders...the whole arranged according to the natural system /by George Don.

1834 v.3

A general history of the dichlamydeous plants :comprising complete descriptions of the different orders...the whole arranged according to the natural system /by George Don.

1838 v.4

A general history of the dichlamydeous plants :comprising complete descriptions of the different orders...the whole arranged according to the natural system /by George Don.

1832 v.2

Enhancing text classification to improve information filtering

Text classification, information filtering, semi-supervised learning, quality control

Partially supervised learning of fuzzy classification rules

Fuzzy classification, semi-supervised learning, data mining

Prototype-based classification and clustering

Magdeburg, Univ., Fak. für Informatik, Habil.-Schr., 2006

Forearm surface EMG signals recognition and muscoloskeletal system dynamics identification using intelligent computational methods

Biosignals processing, Biological Nonlinear and time-varying systems identification, Electomyograph signals recognition, Pattern classification, Fuzzy logic and neural networks methods

Visual analysis, clustering, and classification of contrast-enhanced tumor perfusion MRI data

Magdeburg, Univ., Fak. für Inf., Diss., 2014

Methodenvalidierung zum Nachweis von Pestiziden in fetthaltigen Lebensmitteln nach QuEChERS mittels LC-MS/MS-Verfahren

Die Arbeit befasst sich mit der Vslidierung einer analytischen Methode zur Bestimmung von Pflanzenschutzmittelrückständen in fetthaltigen Lebensmitteln. Dazu erfolgte die Anpassung der QuEChERS-Methode, welche zuvor bei dem SGS Institut Fresenius nur für nicht fetthaltige Lebensmittel angewendet wurde. Vorgestellt wird die Validierung von drei Pstizid-Analyten in den Lebensmittelmatrices Sonnenblumenöl und Kürbiskerne. Die Proben wurden mit der angepassten QuEChERS-Methode aufgearbeitet und mittels Kopplung von Flüssigchromatographie und Massenspektrometrie analysiert

Economic impacts of alternative water policy scenarios in the Spanish production system: an input-output analysis

The objective of this paper is to analyse the economic impacts of alternative water policies implemented in the Spanish production system. The methodology uses two versions of the input-output price model: a competitive formulation and a mark-up formulation. The input-output framework evaluates the impact of water policy measures on production prices, consumption prices, intermediate water demand and private welfare. Our results show that a tax on the water used by sectors considerably reduces the intermediate water demand, and increases the production and consumption prices. On the other hand, according to Jevons' paradox, an improvement in technical efficiency, which leads to a reduction in the water requirements of all sectors and an increase in water production, increases the amount of water consumed. The combination of a tax on water and improved technical efficiency takes the pressure off prices and significantly reduces intermediate water demand. JEL Classification: C67 ; D57 ; Q25. Keywords: Production prices; Consumption prices; Water uses; Water policy; Water taxation.

Generic object classification for autonomous robots

Un dels principals problemes de la interacció dels robots autònoms és el coneixement de l'escena. El reconeixement és fonamental per a solucionar aquest problema i permetre als robots interactuar en un escenari no controlat. En aquest document presentem una aplicació pràctica de la captura d'objectes, de la normalització i de la classificació de senyals triangulars i circulars. El sistema s'introdueix en el robot Aibo de Sony per a millorar-ne la interacció. La metodologia presentada s'ha comprobat en simulacions i problemes de categorització reals, com ara la classificació de senyals de trànsit, amb resultats molt prometedors.

Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.