論文翻譯《Background modeling methods in video analysis: A review and comparative evaluation》
Abstract 前景檢測方法可以有效地將前景對象（包括運動或靜態對象）與背景區分開來，這在視頻分析尤其是視頻監控應用中具有重要意義。一個良好的背景模型可以獲得良好的前景檢測結果。雖然已經提出了很多背景建模方法，但是對它們的綜合評價卻很少。這些方法面臨着光照變化和動態背景等諸多挑戰。本文首先分析了各種背景建模方法在視頻分析應用中的優缺點，然後從質量和計算成本兩方面比較了它們的性能。使用Change
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相關文章
- 1. HMM, MEMM, and CRF: A Comparative Analysis of Statistical Modeling Methods
- 2. 翻譯：Vehicle Detection on a Video Traffic Scene: Review and New Perspectives
- 3. Paper：《Graph Neural Networks: A Review of Methods and Applications》翻譯與解讀
- 4. Dimensionality Reduction_ A Comparative Review
- 5. 【文獻閱讀1】Comparative cytological and transcriptomic analysis of pollen development in autotetraploid a
- 6. 論文：Automated Vehicle Detection and Classification: Models, Methods, and Techniques翻譯（五）
- 7. 論文：Automated Vehicle Detection and Classification: Models, Methods, and Techniques翻譯（三）
- 8. 論文：Automated Vehicle Detection and Classification: Models, Methods, and Techniques翻譯（四）
- 9. Video processing systems and methods
- 10. 【論文翻譯】EIDETIC 3D LSTM: A MODEL FOR VIDEO PREDICTION AND BEYOND