Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/6631
Author(s): Maria João M. Vasconcelos
João Manuel R. S. Tavares
Title: Human motion analysis: methodologies and applications
Issue Date: 2008
Abstract: The study of motion is one of the most interesting areas in Computational Vision, particularly the human motion research. During these last decades several works were presented regarding this subject. Human motion analysis is complex, non-linear and time variant and its tracking can be done using Computational Vision through, for example, human modeling.In order to make human motion analysis more computational tractable, some assumptions are often made. For instance: regarding to movements involved, if the images have one or more persons in the workspace at the same time, if the cameras are static or not or the subject remains inside the workspace being acquired; regarding the environment, if light conditions are constant, the background is static and uniform or not; and regarding the subject in analysis, if its shape and motion are known, if has special markers or clothes.In this work, we intend to present a review about the computational methodologies used in human motion, their advantages and disadvantages and some of their main applications. The study of human motion in image sequences usually follows a general framework: feature extraction, feature correspondence and high-level processing. Feature extraction is related to human motion modeling; these models can be built using stick figures, 2D contours or volumetric models. In feature correspondence the problem of matching two features between two consecutive image frames is approach; one of the difficulties here is to treat occlusion problems that may occur. After the features are extracted and correctly matched over an image sequence, high-level processing can be used, for instance, in the recognition of human movements or activities.As examples of human motion applications we can refer: human recognition in surveillance systems; motion analysis in clinical studies, for example, on orthopedic patients; biomechanical study of athletes, in order to improve their performances; gait classification.
Subject: Engenharia
Engineering
URI: https://repositorio-aberto.up.pt/handle/10216/6631
Source: CMBBE 2008
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: restrictedAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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