Understanding human behaviors is a challenging problem in computer vision that has
recently seen important advances. Human behavior understanding combines image and …

Video, rich in visual real‐time content, is however, difficult to interpret and analyse. Video
collections necessarily have large data volume. Video analytics strives to automatically …

One trend in the recent healthcare transformations is people are encouraged to monitor and
manage their health based on their daily diets and physical activity habits. However, much …

Manifold learning has been effectively used in computer vision applications for
dimensionality reduction that improves classification performance and reduces …

Hidden Markov models (HMMs) provide joint segmentation and classification of sequential
data by efficient inference algorithms and have therefore been employed in fields as diverse …

Clothing changes and lack of data labels are both crucial challenges in person ReID. For the
former challenge, people may occur multiple times wearing different clothes. A majority of …

There are many exercises which are repetitive in nature and are required to be done with
perfection to derive maximum benefits. Sun Salutation or Surya Namaskar is one of the …

Hidden Markov model (HMM) has been widely applied in human action recognition. In this
paper an extension of HMM called fuzzy hidden Markov model (fuzzy HMM) is used for …

In the field of human behavior recognition, a GMM-HMM system shows lower classification
performance in short image sequences. The SVM-HMM, which has been successfully used …

Qu'il tente de prévenir la chute d'une personne âgée, de traduire la langue des signes ou de
contrôler un humain virtuel, l'analyse de gestes est un vaste domaine de recherche qui s' …