Image Segmentation in Video Sequences: A Probabilistic Approach
University of California, Berkeley
Abstract
"Background subtraction" is an old technique for finding moving objects in a video sequence for example, cars driving on a freeway. The idea is that subtracting the current image from a timeaveraged background image will leave only nonstationary objects. It is, however, a crude approximation to the task of classifying each pixel of the current image; it fails with slow-moving objects and does not distinguish shadows from moving objects. The basic idea of this paper is that we can classify each pixel using a model of how that pixel looks when it is part of different classes. We learn a mixture-of-Gaussians classification model for each pixel using an unsupervised technique- an efficient, incremental version of…
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2Topics & keywords
- Artificial intelligence
- Computer vision
- Segmentation
- Computer science
- Probabilistic logic
- Image segmentation
- Scale-space segmentation
- Image (mathematics)
- Sustainable cities and communities