由於行動通訊的普及與影像監控應用內容的多元，促進了一對多即時影像傳輸與遠端行動監控的需求。例如家長可透過行動通訊裝置隨時隨地監看子女於托嬰中心或學校的狀況，社區住戶亦可隨時隨地監看住家環境周遭狀況，這些應用情境都有其共通點：(1)一對多所組成的網路監控環境: 只有一個影音傳送端，但同時有多個影音接收端，(2)接收端的硬體裝置與網路環境彼此差異性極大: 有些接收端可能以3G， 有些透過WIFI進行影音傳輸； 再則因電力或處理速度等因素，部分接收端無法即時解碼或播放影像。異質性網路環境中，網路資源與行動裝置的差異性擴大，促進了影像解析度轉換的需求，若採用固定單一解析度傳輸，對於網路頻寬資源容易形成浪費，降低影音傳輸品質。目前市售DropCam 與IPCam雖針對上述網路環境， 從事多點即時影音監控傳輸，但並未提出任何有關網路環境因應方法，無法適度分配有限的網路資源與有效控制影音傳輸頻寬，當連線人數上升時，影音傳輸效能卻逐漸下滑，喪失一對多即時監控之目的。為解決一對多影像監控傳輸品質， 並同時滿足最多數目接收端之公平監看原則， 本方法提出分數決策矩陣(Weight Decision Matrix)與動態轉換控制流程， 參考(1)傳送端(Dropcam)可承載頻寬， (2)影音參數切換成本與影響連線人數， (3)接收端之優先監看等級， (4)接收端網路下行傳輸效能等四個主要影響傳輸品質參數，透過動態資源分配，決定一影像解析度以滿足傳輸影像需求，提升網路多媒體即時影音傳輸速度及品質。

Due to mobile communication and video surveillance application takes off, demand for one -to-many real time video transmission and remote mobile surveillance is getting more attention. For instance, parents watch their kids in Baby-sitting Center and kindergarten through mobile devices. The community will not only rely on Guardhouse for home security, but monitor security status through mobile devices anytime and anywhere as well. All of these application scenarios have some commons such as one -to-many remote video surveillance through network; video receivers have heterogeneous networks such as 3G or WIFI, which can result in unnecessary waste of network bandwidth. In addition,an unacceptable video quality is transmitted
due to different encoding/decoding capability on mobile device and network env ironment. Although most DropCams claim concurrent multiple video viewers support, the transmission efficiency is getting lower when viewers become more because the system is unable to adaptively control network bandwidth and resource. In order to maintain the transmitted video quality; at the same time, fulfill all viewers’ deman ds for real time video transmission, the paper proposes Weight Decision Matrix and an adaptive video resolution conversion procedure. Four main factors, which affect the quality of one-to-many video transmission most, are considered in Weight Decision Matrix for video resolution conversion. As result, the adaptive video resolution conversion not only fulfills the largest number of mobile surveillance requests, but also provides the better -off video quality under limited network resource.