Background subtraction, although being a very well-established field, has required
significant research efforts to tackle unsolved challenges and to accelerate the progress …

Recurrent neural network (RNN) and long short-term memory (LSTM) have achieved great
success in processing sequential multimedia data and yielded the state-of-the-art results in …

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 …

Object detection is a significant issue in visual surveillance. Faster region-based
convolutional neural network (R-CNN) is a typical object detection algorithm of deep …

Moving shadow elimination plays an important role in the field of moving object detection.
However, the accuracy of shadow elimination is an open question, due to illumination and …

This paper provides a benchmark of the performance of 23 classical and state-of-the-art
background subtraction (BS) algorithms on visible range and near infrared range videos in …

In video-based tracking and recognition applications, shadows are usually mis-classified as
foreground or part of it due to its close associative to the objects. Shadows in indoor …

Shot detection is widely used in video semantic analysis, video scene segmentation, and
video retrieval. However, this is still a challenging task, due to the weak boundary and a …

The objective of this study is to compare several change detection methods for a monostatic
camera and identify the best method for different complex environments and backgrounds in …

Background subtraction is a crucial stage in many visual surveillance systems. The prime
objective of any such system is to detect local changes, and the system could be utilized to …