Abstract—In video surveillance, detection of moving objects from an image sequence is very important for target tracking, activity recognition, and behavior understanding. Background subtraction is a very popular approach for foreground segmentation
Souvenir shops in many of the cities I visit sell posters depicting the world from the local perspective. Landmarks and famous watering holes appear prominently in the foreground. The background features the rest of the planet in progressively less
Chapter 1, Sample Code This chapter is designed to allow you to quickly experiment with and use μC/OS-II. The chapter starts by showing you how to install the distribution diskette and describe the directories created. I then explain some of the cod
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Table of Contents 1. Introduction....................................................................................................................................................2 1.1 What's Special About UNIX?....................................
This paper proposes a novel method for detection and segmentation of foreground objects from a video which contains both stationary and moving background objects and undergoesboth gradual and sudden “once-off” changes. A Bayes decision rule for clas
This paper proposes a novel method for detection and segmentation of foreground objects from a video which contains both stationary and moving background objects and undergoes both gradual and sudden “once-off” changes. A Bayes decision rule for cla
We present a method to extract foreground object regions efficiently from image sequences. Scale-invariant feature transform algorithm is adopted to estimate the descr iptor firstly by matching between two consecutive frames. Given local descr iptor
