Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...

Multiple Sclerosis (MS) is a chronic central nervous system (CNS) demyelinating disease. Gait abnormalities are common and disabling in patients with MS with limited treatment options available. Emerging evidence suggests a role of prefrontal attention networks in modulating gait. High-frequency repetitive transcranial magnetic stimulation (rTMS) is known to enhance cortical excitability in sti...

Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...

Abstract—This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the ...

Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...

OBJECTIVES For several years, the concept of "physiological senile gait" has been strongly contested and seems to be associated with abnormal gait. Indeed, some changes characteristic of senile gait appear early on in subjects with neurodegenerative pathologies. The aim of this article was to determine how recent contributions can improve the study of gait in old populations. This paper is a th...

Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...

Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...

Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...

Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...