全自動即時量測系統將成為未來測量發展方向之一。而以近景攝影為基礎的測量車系統將成為第一波即時系統的發展標的。在近景攝影測量工程之中人工介入最多的部分，莫過於轉點的量測。因此如何全自動進行轉點量測是達成全自動化的基礎工程。現有近景自動化轉點量測方法多為高階資訊的匹配，多應用在長基線的影像匹配中。但近年來數位視訊逐漸普及，影像品質亦日漸提升，其挾著大量且快速取得資料的特性，逐漸受到測量界的重視，使得短基線影像匹配也成為研究重點之一。本研究中以數位攝影機做為近景攝影的工具，測量車的應用環境—街道、建築物作為測試對象，測試光流法及NCC法對於短基線特徵物追蹤的效果及品質，並進行分析測試。
本研究中針對數位視訊設計出一套特徵點自動化萃取、量測、追蹤、偵錯的流程，而這套流程能搭配任何以點為基礎的追蹤方式。研究中將測試的環境分為兩類，第一類為全3D的環境，另一類則為近似2D牆面上的特徵。在移動數位攝影機來拍攝靜止景物的情況下，分別進行左右移動拍攝、前後移動拍攝、以及圍繞物體拍攝之同名點追蹤。各自分析上述狀況下的成功追蹤率及套合精度後，以上述成果分析、比較光流及NCC兩種演算法之優缺點及適用性。
此外，本研究也提出一新方法來改良傳統光流法之功能，使得最大追蹤距離顯著改善，且在追蹤成果的可靠性方面也有所提昇。在本文實驗例中，此新方法使成功追蹤的範圍從傳統光流法3～4像元提高至30像元以上。
再者，研究成果顯示本流程足以提供全自動製作鑲嵌圖之應用。但在提供空三平差用途方面，須待次像元精度點位量測及新增追蹤點位原則兩方面有所改進後，方可實現。

Automatic real-time surveying system is one of the developments in the field of surveying, while mobile mapping vehicle system based on close range photogrammetry becomes a primary research topic. Point transfer of the close-range photogrammetry requires the most manual operations. Thus, how to automate the point transfer becomes the foundation of the achieving real-time surveying. There are several automatic point transfer methods. However, most of them are used for matching high-level information in wide baseline applications. Recently, digital video becomes important in surveying because of its popularity, improved quality, and characteristics of gathering images rapidly and in quantity. These characteristics of digital video make short baseline image matching becoming one of the major research topics of Automatic Real-Time Surveying system. This research uses digital video as the tool of close-range photogrammetry, the environment of mobile mapping vehicle, such as streets and buildings, as targets. The effectiveness and quality of surveying optical flow method and NCC method and their results as well is to be analyzed and studied.
In this study, a new flowchart is designed for automatic extracting, measuring, tracking, and error detection of the feature points in digital video. This flowchart may be used with any point-based tracking method. The surveying environment is divided into two categories: (1) the fully 3-D environment and (2) the 2-D wall surface characteristics. For still targets, digital videos are took by moving the video camcorder from left to right, from fore to aft, and surrounding the targets. The tracking rate and the image matching accuracy of digital video images were analyzed. The results were then used for comparing the advantages and suitability of optical flow method and NCC method.
In addition, a new method is developed and presented to improve the function of traditional optical flow method. Test results show clearly that it significantly increases the maximum tracking distance and improves the reliability of the tracking results. The tracking range was increased from 3-4 pixels in traditional optical flow method to more than 30 pixels using the new method.
Also, the results indicate that the new flowchart is useful for automatic mosaic generation using digital video images. However, both DV-image matching approaches with sub-pixel accuracy and rules for adding new tracking points still ought to be further studied before the new method can be used in aerial triangulation applications.

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