The main objective of this paper is to develop multiple human object tracking approach based on motion estimation and detection, background subtraction, shadow removal and occlusion detection. A reference frame is initially used and considered as background information. While a new object enters into the frame, the foreground information and background information are identified using the refer...

Moving object segmentation has its own niche as an important topic in computer vision. It has avidly being pursued by researchers. Background subtraction method is generally used for segmenting moving objects. This method may also classify shadows as part of detected moving objects. Therefore, shadow detection and removal is an important step employed after moving object segmentation. However, ...

We present an application of Viola-Jones face detection and exemplar-based inpainting to automatically select and remove unwanted background person(s) in photographs. We experiment with using various source and target region masks as well as patch and neighbourhood selections to produce realistic inpaintings. The final pipeline is able to generate results comparable to those achieved with manua...

Cluttered background removal in static images with mild occlusion remains still a challenging task for object identification or classification problems. In most of the real-world images, vehicle objects with cluttered background containing trees, road views, buildings, people, etc tent to be a noisy data or leads to the problem of clarity. The background feature covers the major portion of the ...

A computer vision technique is introduced to remove a moving foreground object in a video sequence for digital post-processing. Recently various digital special effects are employed in generating video production. This paper introduces one of the digital special effect techniques, moving object removal and background completion. To find a moving foreground object in a video sequence, we track b...

This paper describes a new technique for removing the background level from digital images produced in comprehensive two-dimensional gas chromatography (GCxGC). Background removal is an important first step in the larger problem of quantitative analysis. The approach estimates the background level across the chromatographic image based on structural and statistical properties of GCxGC data. The...

Quantitative Susceptibility Mapping (QSM) is an emerging Magnetic Resonance Imaging (MRI) technique that provides in-vivo measurements of the magnetic susceptibility of, e.g., brain tissue. In practice, QSM requires solving a series of challenging inverse problem. Here, we will address two important steps, the removal of the background field, which is caused by sources outside the Region of Int...

The removal of the background magnetic field is a critical step in generating phase images and quantitative susceptibility maps, which have recently been receiving increasing attention. Although it is known that the background field satisfies Laplace's equation, the boundary values of the background field for the region of interest have not been explicitly addressed in the existing methods, and...

Background estimation and removal based on the joint use of range and color data produces superior results than can be achieved with either data source alone. This is increasingly relevant as inexpensive, real-time, passive range systems become more accessible through novel hardware and increased CPU processing speeds. Range is a powerful signal for segmentation which is largely independent of ...