Human activity recognition is an important area of computer vision research. Its applications
include surveillance systems, patient monitoring systems, and a variety of systems that …

This survey reviews advances in human motion capture and analysis from 2000 to 2006,
following a previous survey of papers up to 2000 [TB Moeslund, E. Granum, A survey of …

Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …

In this work, we introduce a new video representation for action classification that
aggregates local convolutional features across the entire spatio-temporal extent of the video …

In this paper we present a method to capture video-wide temporal information for action
recognition. We postulate that a function capable of ordering the frames of a video …

Human activity recognition (HAR) is a complex and multifaceted problem. The research
community has reported numerous approaches to perform HAR. Along with HAR …

We propose a function-based temporal pooling method that captures the latent structure of
the video sequence data-eg, how frame-level features evolve over time in a video. We show …

As compared to simple actions, activities are much more complex, but semantically
consistent with a human's real life. Techniques for action recognition from sensor generated …

This paper provides a comprehensive survey for activity recognition in video surveillance. It
starts with a description of simple and complex human activity, and various applications. The …

In this work, we aim to address the problem of human interaction recognition in videos by
exploring the long-term inter-related dynamics among multiple persons. Recently, Long …