Background modeling has emerged as a popular foreground detection technique for various
applications in video surveillance. Background modeling methods have become increasing …

The rising demand for surveillance systems naturally necessitates more efficient and noise
robust moving object detection (MOD) systems from the captured video streams. Inspired by …

The spatially distributed digital cameras in Wireless Multimedia Sensor Networks (WMSN)
are provided with miniature batteries resulting in power constraints. These cameras acquire …

Background modeling is a crucial step in various computer vision applications such as video
surveillance, object tracking, and moving object detection. Classifying image pixels as …

As a widely-used method in the image categorization tasks, the Bag-of-Words (BoW) method
still suffers from many limitations such as overlooking spatial information. In this paper, we …

Abstract Moving Object Detection (MOD) and Background Subtraction (BS) are the
fundamental tasks in video surveillance systems. But, one of the major challenges which …

Scene classification is one of the most significant and challenging tasks in computer vision.
This paper presents a new method for scene classification using bag of visual words and a …

This article proposes a new method for image classification and image retrieval. The
advantages of the proposed method are its high performance and requiring less memory …

Threat assessment of targets is a critical component of combat decision-making. Existing
threat assessment methods only consider specific dimensions of information. When …

Segmenting moving objects from various video streams especially in the presence of
complex dynamic backgrounds is one of the most pivotal and fundamental tasks in computer …