A method of estimating the number of people in crowded scenes was proposed based on energy of the foreground image in the frequency domain. Firstly, the foreground image including the target area was obtained by background subtraction. And furthermore, with the second order wavelet decomposition of the foreground image, the energy of high frequency sub-band was computed. Finally, by analyzing t...

A method is developed to distinguish between cars and trucks present in a video feed of a highway. The method builds upon previously done work using covariance matrices as an accurate descriptor for regions. Background subtraction and other similar proven image processing techniques are used to identify the regions where the vehicles are most likely to be, and a distance metric comparing the ve...

A new robust method to segment foreground regions from color video sequences using multiple thresholds and morphological processes is proposed. Background models are observed for a long time, and their mean and standard deviation are used for background subtraction. Shadow regions are eliminated using color components, and the final foreground silhouette is extracted by smoothing the boundaries...

We propose a region-based method to extract foreground regions from colour video sequences. The foreground region is decided by voting with scores from background subtraction to the sub-regions by graphbased segmentation. Experiments show that the proposed algorithm improves on conventional approaches especially in strong shadow regions.

Background subtraction is a commonly used class of techniques for segmenting out objects of interest in a scene for applications such as surveillance. This paper surveys a representative sample of the published techiques for background subtraction, and analyses them with respect to three important attributes: foreground detection; background maintenance; and postprocessing.

Background subtraction is a common method for detecting moving objects from static cameras able to achieve real-time performance. However, it is highly dependent on a good background model particularly to deal with dynamic scenes. In this paper a novel real-time algorithm for creating a robust and multimodal background model is presented. The proposed approach is based on an on-line clustering ...

Environmental monitoring applications present a challenge to current background subtraction algorithms that analyze the temporal variability of pixel intensities, due to the complex texture and motion of the scene. They also present a challenge to segmentation algorithms that compare intensity or color distributions between the foreground and the background in each image independently, because ...