object detection plays an important role in successfulness of a wide range ofapplications that involve images as input data. in this paper we have presented anew approach for background modeling by nonconsecutive frames differencing.direction and velocity of moving objects have been extracted in order to get anappropriate sequence of frames to perform frame subtraction. stationary parts ofbackg...

This paper proposes a feature-based multi-sensor fire detector operating on ordinary video and long wave infrared (LWIR) thermal images. The detector automatically extracts hot objects from the thermal images by dynamic background subtraction and histogram-based segmentation. Analogously, moving objects are extracted from the ordinary video by intensity-based dynamic background subtraction. The...

This paper presents a statistical method to subtract background in maximum likelihood fit, without relying on any separate sideband or simulation for background modeling. The method, called sFit, is an extension to the sPlot technique originally developed to reconstruct true distribution for each date component. The sWeights defined for the sPlot technique allow to construct a modified likeliho...

We propose a novel feature, local histogram of figure/ground segmentations, for robust and efficient background subtraction (BGS) in dynamic scenes (e.g., waving trees, ripples in water, illumination changes, camera jitters, etc.). We represent each pixel as a local histogram of figure/ground segmentations, which aims at combining several candidate solutions that are produced by simple BGS algo...

In this paper, we present a novel foreground extraction method that automatically identifies image regions corresponding to a common space region seen from multiple cameras. We assume that background regions present some color coherence in each image and we exploit the spatial consistency constraint that several image projections of the same space region must satisfy. Integrating both color and...

Automatic segmentation of foreground from background in video sequences has attracted lots of attention in computer vision. Two different implementations have been completed during the summer. The first one is known as “background subtraction”. The foreground is segmented from the background by directly subtracting a mean background image B from each frame, and retaining those parts of the fram...