Understanding the activities of human from videos is demanding task in Computer Vision.
Identifying the actions being accomplished by the human in the video sequence …

Deep learning based subspace clustering networks have been a significant technique for
motion segmentation, unsupervised image segmentation, image representation and …

This paper tackles the problem of human action recognition, defined as classifying which
action is displayed in a trimmed sequence, from skeletal data. Albeit state-of-the-art …

In the past decade, human activity recognition (HAR) has grown in popularity due to its
applications in security and entertainment. As recent years have witnessed the emergence …

Convolutional neural network (CNN) depicts the transformation of the input image through a
series of convolutions and other non-linear phases for recognition and classification …

Abstract Structural Health Monitoring (SHM) aims to give a diagnosis of the “state” of the
constituent materials, different parts, and full assembly of the structure as a whole. The …

This thesis introduces the recent advances on decomposition into low-rank plus sparse
matrices and tensors, as well as the main contributions to face the principal issues in moving …

Human Activity Recognition (HAR) has wide applications in surveillance, assisted living and
robotic systems that interact with people. Traditional methods for HAR usually input source …

Activity recognition systems have been found to bevery effective for tracking users' activities
in research areas like healthcare and assisted living. Wearable accelerometers that can …

Assistive living has gained increased focus in recent years with the increase in elderly
population. This has led to a desire for technical solutions to reduce cost. Learning to …