A Genetic Algorithm-Based Moving Object Detection for Real-time Traffic Surveillance

作者：Lee Giyoung^*; Mallipeddi Rammohan; Jang Gil Jin; Lee Minho

来源：IEEE Signal Processing Letters, 2015, 22(10): 1619-1622.

DOI：10.1109/LSP.2015.2417592

• Background subtraction
• dynamic saliency map
• genetic algorithm
• object detection
• real-time traffic surveillance system

Recent developments in vision systems such as distributed smart cameras have encouraged researchers to develop advanced computer vision applications suitable to embedded platforms. In the embedded surveillance system, where memory and computing resources are limited, simple and efficient computer vision algorithms are required. In this letter, we present a moving object detection method for real-time traffic surveillance applications. The proposed method is a combination of a genetic dynamic saliency map (GDSM), which is an improved version of dynamic saliency map (DSM) and background subtraction. The experimental results show the effectiveness of the proposed method in detecting moving objects.

• 出版日期2015-10