Motion detection in complex environments by genetic programming

ABSTRACT

Detecting motions is an important aspect of machine vision. However real world vision tasks often contain interfering motion information which is not of interest. To tackle this difficult task, we adapted Genetic Programming into this domain. The GP-based methodology presented in this paper does not require the implementation of existing motion detection algorithms. The evolved programs can detect genuine moving objects such as cars and boats, while ignoring background movements such as waving trees, rippling water surface and even pedestrians. These programs provide reliable performance under different lighting conditions, either indoors and outdoors. Furthermore no preprocessing of video input is required which is usually mandatory in conventional vision approaches.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.8 Scene Analysis
          Subjects: Motion

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.10 Vision and Scene Understanding
            Subjects: Video analysis

General Terms:
Algorithms, Design, Experimentation

Keywords:
genetic programming, motion detection, tracking, video analysis