Analyzing crowd events in a video is key to understanding the behavioral characteristics of
people (humans). Detecting crowd events in videos is challenging because of articulated …

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 …

Networks are known as perfect tools for modeling various types of systems. In the literature
of network mining, frequent subgraph mining is considered as the essence of mining …

In this paper, we propose a new multi-layer Fisher vector encoding method based on
trajectory descriptors for human action recognition. The proposed method aims at improving …

During the last few years, object recognition has received a big of interest in an attempt to
make use of the large scale image datasets. Object recognition allows understanding image …

The authors propose ISEQL, a language based on relational algebra extended by intervals
for detecting high-level surveillance events from a video stream. The operators they …

In recent years, semantic segmentation has become one of the most active tasks of the
computer vision field. Its goal is to group image pixels into semantically meaningful regions …

In the computer vision field, semantic segmentation represents a very interesting task.
Convolutional Neural Network methods have shown their great performances in comparison …

In recent years, Computer vision has become a very active field. This field includes methods
for processing, analyzing, and understanding images. The most challenging problems in …

We propose a language based on relational algebra extended by intervals for detecting high-
level surveillance events from a video stream. The operators we introduce for describing …