Computer vision applications based on videos often require the detection of moving objects
in their first step. Background subtraction is then applied in order to separate the background …

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

Background subtraction is an important task for visual surveillance systems. However, this
task becomes more complex when the data size grows since the real-world scenario …

Background subtraction is an effective method of choice when it comes to detection of
moving objects in videos and has been recognized as a breakthrough for the wide range of …

Moving object segmentation (MOS) is the process of identifying dynamic objects from video
frames, such as moving vehicles or pedestrians, while discarding the background. It plays …

Multi-band polarization imaging, by mean of analyzing spectral and polarimetric data
simultaneously, is a good way to improve the quantity and quality of information recovered …

In this paper, we follow the trend of deep learning and make an attempt to investigate the
potential benefit of using multispectral images via convolutional neural networks for …

We present a new statistical approach combining temporal and spatial information for robust
online background subtraction (BS) in videos. Temporal information is modeled by coupling …

In this article, we have introduced a novel system design framework for dynamic, data-driven
processing of multispectral video streams using LD techniques. The framework is motivated …

Spectral filter array (SFA) technology requires development on demosaicing. The authors
extend the linear minimum mean square error with neighborhood method to the spectral …