In this paper, a pixel-based background modeling method, which uses nonparametric kernel density estimation, is proposed. To reduce the burden of image storage, we modify the original KDE method by using the first frame to initialize it and update it subsequently at every frame by controlling the learning rate according to the situations. We apply an adaptive threshold method based on image cha...

We present a frame-synchronous noise compensation algorithm that uses Stochastic Matching approach to cope with time-varying unknown noise. This method proposes to estimate simple mapping function in parallel with Viterbi alignment. The technique is entirely general since no assumption is made on the nature, level and variation of noise. Our algorithm is evaluated on the VODIS database recorded...

The aim of this paper is to detect abnormal events in video streams, a challenging but important subject in video surveillance. A novel algorithm is proposed to address this problem. The algorithm is based on an image descriptor and a nonlinear classification method. The images are subjected to Otsu’s method for global thresholding. A histogram of optical flow orientation as a descriptor encodi...

In this paper, we present a grid-based tracking by detection methodology, applied to 3D people tracking for multi-camera video surveillance. In particular, frame-by-frame detection is performed by means of hierarchical likelihood grids, using edge matching through the oriented distance transform on each camera view and a simple person model, followed by likelihood grids clustering in state-spac...

In this paper we present a new method for object tracking initialization using background subtraction. We propose an effective scheme for updating a background model adaptively in dynamic scenes. Unlike the traditional methods that use the same “learning rate” for the entire frame or sequence, our method assigns a learning rate for each pixel according to two parameters. The first parameter dep...

As the elderly population increases globally, demand for systems and algorithms that target is increasing. Focusing on extendibility of smart mirrors, our purpose to create a motion detection system based video input by an attached device (an RGB camera). The presented in this paper algorithm returns Boolean value indicating skeletal information. We analyzed problems occur when adjacent frame s...

this paper is a continuation of [uniformities and covering properties for partial frames (i)], in which we make use of the notion of a partial frame, which is a meet-semilattice in which certain designated subsets are required to have joins, and finite meets distribute over these. after presenting there our axiomatization of partial frames, which we call $sels$-frames, we added structure, in th...

A vehicle tracking and grouping algorithm is presented in this work using Lukas-Kanade Tracking technique. Every frame of the sequence is downsampled to improve efficiency. A section of the highway is marked to establish a detection zone where the detection and tracking of the features take place. For every frame a background subtraction is done and only the foreground pixels inside the detecti...

Abstract This report proposes a design method of a digital filter to detect running water region in video signal. As a result of applying this filter, the water level of a river is automatically detected as a boundary between the land region and the water region. Conventional approaches have used the edge detector "vertically" to extract a horizontal line as running water surface. The frame "su...

“Background maintenance and subtraction” is an important problem for many computer vision applications. This paper proposes a novel model for background. This model includes two components and it processes the video sequence at pixel level and frame level alternatively. The advantage of this model is that it can capture both the temporal and spatial context of the video sequence. At pixel level...