近年來，自行車幾乎已成為全民運動，然而由於其安全性較差，發生事故時往往會造成嚴重的後果。本研究結合自行車、攝影機及手持運算裝置等三方裝置，透過電腦視覺技術偵測後方靠近之來車，並主動提醒使用者，提升行車時之安全性。針對後車靠近偵測技術，本研究透過少量特徵點的光流追蹤，並結合隨機抽樣一致性演算法(RANSAC)來估測相鄰畫面之單應性矩陣，以對齊相鄰畫面並透過影像相減法來取出移動前景，此外針對落於此前景區塊內之特徵點，再次進行光流法的追蹤，透過攝影機幾何之消失點特性，來消除假警報並有效偵測出往攝影機靠近之移動車輛。本系統已成功實作於iPhone 4平台上，且在一般市區影片中證實系統之可行性及演算法之有效性。

In recent years, biking has been popular and getting more and more attention in many country.However, because of its poor protectability, the accident will often result in serious consequences. This studycombines a bicycle, a camera and a handheld computing device, and applies a vision-basedapproaching-vehicle detection algorithm to remind driver to “watch” his/her back. For the approaching-vehicledetection algorithm, firstly, the optical flow estimation is applied to track a small number of feature points.These tracked points are utilized to estimate the homography transform between two consecutive frames byusing RANdom SAmple Consensus algorithm (RANSAC). Therefore, two consecutive frames can be alignedand moving foreground can thus be extracted by performing image subtraction. Once again, feature pointswithin the moving foreground are tracked and weighted by the camera geometry of vanishing point. Theweighting procedure eliminates false alarms and effectively detects the vehicles which are approaching thecamera. The system has been successfully implemented on the iPhone platform, and validated the feasibilityof the system and the effectiveness of the algorithm in the general urban scenario.