This paper introduces an efficient video representation method based on the dense
trajectory motion map (DTM). We utilize the salient features of dense trajectories and motion …

The dense trajectories and low‐level local features are widely used in action recognition
recently. However, most of these methods ignore the motion part of action which is the key …

In human activity recognition system both static and motion information play crucial role for
efficient and competitive results. Most of the existing methods are insufficient to extract video …

We propose a unified method for recognizing human action and human related events in a
realistic video. We use an efficient pipeline of (a) a 3D representation of the Improved Dense …

Recognition of human actions in videos has been an active research area in computer
vision community due to its important theoretical research significance and extensive …

Recently, a common and popular method that produces competitive accuracy is to employ
dense trajectories to identity human action. However, computing descriptors of dense …

This article presents a new method for video representation, called trajectory based 3D
convolutional descriptor (TCD), which incorporates the advantages of both deep learned …

Action recognition methods enable several intelligent machines to recognize human action
in their daily life videos. Indeed, many action recognition methods give a noticeable …

Spatiotemporal features have significant importance in human action recognition, as they
provide the actor's shape and motion characteristics specific to each action class. This paper …

As a popular research field in computer vision community, human action recognition in
videos is a challenging task. In recent years, trajectory based methods have been proven …