Human gait is the basic form of human locomotion and the most comfortable and economical way of movement in short distances [1,2]. Despite complex neural control the gait characterises with smooth and repeatable movements in human joints, which can be recorded by cinematographic methods. In the clinical applications gait stereotype is frequently used in human motion analysis to compare the obta...

Gait recognition is an important biometric technique for video surveillance tasks, due to the advantage of using it at distance. In this paper, we present a persistent homology-based method to extract topological features (the so-called topological gait signature) from the the body silhouettes of a gait sequence. It has been used before in several conference papers of the same authors for human...

In a walking cycle design, maximizing the upright balance should be considered in addition to the kinematic constraints, energy consumption rate must be considered. The purpose of this study is to find the optimal step length obtained for each person according to the physical features. In this research, in order to minimize energy consumption rate by considering maximum balance two cost functio...

Psychological studies indicate that people have a small but statistically significant ability to recognize the gaits of individuals that they know. Recently, there has been much interest in machine vision systems that can duplicate and improve upon this human ability for application to biometric identification. While gait has several attractive properties as a biometric (it is unobtrusive and c...

In order to study the mechanisms behind the human motion and its disorders, and to comprehend how do neuromuscular impairments affect the human movements, it is crucial to know the human musculoskeletal system. This knowledge is also essential to effectively model and analyse the musculoskeletal system, and to classify the human movement. With this work we conducted preliminary studies over a m...

We propose a new descriptor for human identification based on gait. The current and most prevailing trend in gait representation revolves around encoding body shapes as silhouettes averaged over gait cycles. Our method, however, captures geometric properties of the silhouettes boundaries. Namely, we evaluate contour curvatures locally using Gauss maps. This results in an improved shape represen...

Human face/gait-based gender recognition has been intensively studied in the previous literatures, yet most of them are based on the same database. Although nearly perfect gender recognition rates can be achieved in the same face/gait dataset, they assume a closed-world and neglect the problems caused by dataset bias. Real-world human gender recognition system should be dataset-independent, i.e...

The quantitative assessment of the change of gait symmetry has played a very important role in the clinical diagnostics. This paper investigated the application of an advanced hybrid machine learning approach such as the combining kernel-based principal component analysis (KPCA) with support vector machine (SVM) to evaluate the change of gait symmetry quantitatively based on the basic idea that...

The ability to predict human gait, particularly impaired human gait, has the potential to improve rehabilitation/training outcomes and to reduce prosthesis/orthosis development costs. This work presents a walking model of moderate complexity that accurately captures both sagittal plane joint kinematics and whole body energetics for healthy human walking. The six-link, left-right symmetric model...

Everyday people will observe, analyze, and interpret the motion and actions of the people surrounding them. This is a source of very valuable information about not only what each person is doing but also things like their intentions, their attitude towards the observer, situations they perceive as dangerous or interesting, etc. In open spaces where people are moving around the type of motion wi...