Understanding human actions in videos has been a central research theme in Computer
Vision for decades, and much progress has been achieved over the years. Much of this …

Recent progress in the field of human action recognition points towards the use of Spatio-
Temporal Interest Points (STIPs) for local descriptor-based recognition strategies. In this …

This is an introduction to multicast routing, which is the study of methods for routing from one
source to many destinations, or from many sources to many destinations. Multicast is …

Most of the existing action recognition methods represent actions as bags of space-time
interest points. Specifically, space-time interest points are detected from the video and …

Action recognition from videos is an important area of computer vision research due to its
various applications, ranging from visual surveillance to human-computer interaction. To …

Recognizing human actions in video sequences has been a challenging problem in the last
few years due to its real-world applications. A lot of action representation approaches have …

Common human actions are instantly recognizable by people and increasingly machines
need to understand this language if they are to engage smoothly with people. Here we …

Searching for specific persons from surveillance videos captured by different cameras,
known as person re-identification, is a key yet under-addressed challenge. Difficulties arise …

Due to the exponential growth of the video data stored and uploaded in the Internet websites
especially YouTube, an effective analysis of video actions has become very necessary. In …

We present a novel structure, called a Subspace Forest, designed to provide an efficient
approximate nearest neighbor query of subspaces represented as points on Grassmann …