以智慧型車流監控系統在可變位元視訊串流下之移動車輛擷取PROBABILISTIC NEURAL NETWORK BASED MOVING OBJECT DETECTION METHOD AND AN APPARATUS USING THE SAME

專利類型

發明

專利國別 (專利申請國家)

美國

專利申請案號

14/052,782

專利證號

US 9,159,137 B2

專利獲證名稱

以智慧型車流監控系統在可變位元視訊串流下之移動車輛擷取PROBABILISTIC NEURAL NETWORK BASED MOVING OBJECT DETECTION METHOD AND AN APPARATUS USING THE SAME

專利所屬機關 (申請機關)

國立臺北科技大學

獲證日期

2015/10/13

技術說明

在交通監控系統中，自動化車輛偵測扮演一個很重要的腳色。在無線通訊系統中，交通攝影機的資料傳遞時常會遭受網路擁塞或是未知頻寬的限制。然而，在這樣的情形下，有效的移動車輛偵測是很困難的。本文提出一個基於機率類神經網路的創新移動車輛偵測方法，此方法可以有效的在低或是高位元的視訊串流下達到精確且完整的移動車輛偵測。透過量化和值化的實驗結果分析可以證明我們的方法有大幅度的勝過其他過去知名的方法，其中在Similarity和F1兩個測試標準下勝過其他知名方法分別高達81.11%和89.39%。 Motion detection plays an important role in video surveillance system. Video communications over wireless networks can easily suffer from network congestion or unstable bandwidth, especially for embedded application. A rate control scheme produces variable bit-rate video streams to match the available network bandwidth. However, effective detection of moving objects in variable bit-rate video streams is a very difficult problem. This paper proposes an advanced approach based on the counter-propagation network through artificial neural networks to achieve effective moving object detection in variable bit-rate video streams. In this paper, we compare our method with other state-of-the-art methods. The overall results show that our proposed method substantially outperforms other state-of-the-art methods by Similarity and F1 accuracy rates of 83.34% and 89.71%, respectively.

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