[[alternative]]應用影像平面中偵測移動物體之方法於機器人單眼視覺式巡航

[[abstract]]This article presents an algorithm for moving object detection (MOD) in robot visual simultaneous localization and mapping (SLAM). This MOD algorithm is designed based on the defining epipolar constraint for the corresponding feature points on image plane. An essential matrix obtained using the state estimator is utilized to represent the epipolar constraint. Meanwhile, the method of speeded-up robust feature (SURF) is employed in the algorithm to provide a robust detection for image features as well as a better description of landmarks and of moving objects in visual SLAM system. Experiments are carried out on a hand-held monocular camera to verify the performances of the proposed algorithm. The results show that the integration of MOD and SURF is efficient for robot navigating in dynamic environments.[[abstract]]本論文發展視覺式移動物體偵測演算法， 並且應用於機器人同時定位與建圖的任務。此移動物體偵測演算法的概念是基於影像特徵在極線的限制條件，亦即影像平面中兩個相對應的特徵點必定受限於所定義的極線方程式。本研究利用狀態估測器進行本質矩陣的求算，再使用本質矩陣描述極線的限制條件。另外，也應用加速強健特徵的影像處理方法於視覺式同時定位與建圖任務中，提供穩定的影像特徵偵測方法，以及地標與移動物體的強健描述方法。本研究使用單眼視覺實現三個測試範例以驗證所發展的演算法之效能，包括同時定位與建圖、移動物體追蹤、以及行人偵測與追蹤等。測試結果顯示本研究整合移動物體偵測與加速強健特徵等方法，可以提供機器人在動態環中順利完成巡航任務。[[notice]]補正完