التفاصيل البيبلوغرافية
| العنوان: |
Case-based background modeling: associative background database towards low-cost and high-performance change detection. |
| المؤلفون: |
Shimada, Atsushi1 atsushi@limu.ait.kyushu-u.ac.jp, Nonaka, Yosuke1 nonaka@limu.ait.kyushu-u.ac.jp, Nagahara, Hajime1 nagahara@ait.kyushu-u.ac.jp, Taniguchi, Rin-ichiro1 rin@ait.kyushu-u.ac.jp |
| المصدر: |
Machine Vision & Applications. Jul2014, Vol. 25 Issue 5, p1121-1131. 11p. |
| مصطلحات موضوعية: |
*VIDEO surveillance, *REMOTE sensing, *IMAGE processing, *PIXELS, *MACHINE theory |
| مستخلص: |
Background modeling and subtraction is an essential task in video surveillance applications. Many researchers have discussed about an improvement of performance of a background model, and a reduction of memory usage or computational cost. To adapt to background changes, a background model has been enhanced by introducing various information including a spatial consistency, a temporal tendency, etc. with a large memory allocation. Meanwhile, an approach to reduce a memory cost cannot provide better accuracy of a background subtraction. To tackle the trade-off problem, this paper proposes a novel framework named 'case-based background modeling'. The characteristics of the proposed method are (1) a background model is created, or removed when necessary, (2) case-by-case model sharing by some of the pixels, (3) pixel features are divided into two groups, one for model selection and the other for modeling. These approaches realize a low-cost and high accurate background model. The memory usage and the computational cost could be reduced by half of a traditional method and the accuracy was superior to the method. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
Academic Search Index |
