本文使用立體視覺原理對目標物進行距離量測，在本研究定義的範圍內其量測的數據具相當的準確。本文提出之方法為利用水平的雙鏡頭攝影機擷取影像，並由相似三角形原理計算距離資訊。在演算過程中，使用者在左側的攝影機畫面裡選取任意之目標物，並利用模板匹配演算法，在右影像區域找出與左影像相似的目標物，再透過像素與公尺之間的單位換算，求出目標物與攝影機之間的實際距離。 電腦立體視覺系統亦應用於行人偵測，並使用HOG運算子於行人特徵之描繪，透過級聯(cascade)分類器分類出行人資訊與否，並針對級聯分類器進行實驗，並探討不同層級之分類器所分類出結果。本文的成果可以為車輛避撞系統建立對行人的識別與警示。

This thesis presents a distance measurement technique using computer stereo vision. The measurement result is quite accuracy within a defined range. The purposed approach sets up two cameras horizontally to capture the images, and adopts the similar triangles theorem to calculate the distance. In the measuring algorithm, the object in the left frame is selected manually to execute the matching algorithm to find the similar feature in right frame. It converts the disparity units into meter units and finally computes the distance of target. The proposed computer stereo vision is applied for human detection. The experiment module is established. A Histogram of Orientated Gradients (HOG) descriptor is used to distinguish the human features through the cascade classifier to determine the object for human beings. The proposed method in this thesis also develops the classifier for experiments. It accomplishes some outstanding contribution to target identification for collision avoidance to pedestrians.

[1] J. Wang, F. Gao, S. Shi, J. Wang, “A New Method for Distance and Relative Velocity Measurement in Vehicle Collision Warning System”, Sixth International Conference on Intelligent Systems Design and Applications (ISDA’06), 2006, pp. 1142-1147.
[2] A. Carullo, M. Parvis, “An Ultrasonic for Distance Measurement in Automotive Applications”, IEEE Journal of Sensors, Vol. 1, No. 3, Oct. 2001, pp. 143-147.
[3] R. A. Hamzah, R. A. Rahim, H. N. Rosly, “Depth Evaluation in Selected Region of Disparity Mapping for Navigation of Stereo Vision Mobile Robot”, IEEE Symposium on Industrial Electronics & Applications (ISIEA), 2010, pp. 551-555.
[4] H. Clemens, H. Matthias, “Measuring Distance with Mobile Phones using Single-Camera Stereo Vision”, 2012 the 32nd International Conference on Distributed Computing Systems Workshops (ICDCSW), 2012, pp. 88-93.
[5] M. C. Lu, W. Y. Wang, C. Y. Chu, “Image-Based Distance and Area Measuring Systems”, IEEE Journal of Sensors, Vol. 6, No.2, 2006, pp. 495-503.
[6] 陳韋戎、盧福明、林達德， “立體視覺系統於距離量測上之應用”，中華農業機械論文發表會論文摘要集，2001，pp. 215-217.
[7] Y. M Musta, R. Noor, H. Hasbi, A. W. Azma, “Stereo Vision Images Processing for Real-Time Object Distance and Size Measurements”, IEEE International Conference on Computer and Communication Engineering (ICCCE), 2012, pp. 659-663.
[8] D. Murray, J. J. Little, “Using Real Time Stereo Vision for Mobile Robot Navigation”, Autonomous Robots, Vol. 8, No.2, 2000, pp. 161-171.
[9] B. Massimo, B. Alberto, “GOLD: A Parallel Real-Time Stereo Vision System for Generic Obstacle and Lane Detection”, IEEE Transactions on Image Processing, Vol. 7, No.1, 1998, pp. 62-81.
[10] H. G. Jung, Y. H. Lee, B. J. Kim, P. J. Yoon, J. H. Kim, “Stereo Vision-Based Forward Obstacle Detection”, International Journal Automotive Technology, Vol. 8, No.4, 2007, pp.493-504.
[11] D. M. Gavrila, V. Philomin, "Real-time Object Detection for Smart Vehicle", Proceedings of the Seventh IEEE International Conference on Computer Vision, Vol. 1, 1999, pp. 87-93.
[12] D. M. Gavrial, “Pedestrian Detection from a Moving Vehicle”, Springer Berlin Heidelberg in Computer Vision, ECCV 2000, pp. 37-49.
[13] N. Dalal, B. Triggs, “Histograms of Oriented Gradients for Human Detection”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, Vol. 1, 2005, pp. 886-893.
[14] X. Wang, T. X. Han, S. Yan, “An HOG-LBP Human Detector with Partial Occlusion Handling”, IEEE 12th International Conference on Computer Vision, 2009, pp. 32-39.
[15] Q. Zhu, M. C. Yeh, K. T. Cheng, “Fast Human Detection using a Cascade of Histograms of Gradients”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2006, pp. 1491-1498.
[16] Axis Communication, CCD and CMOS sensor technology, available in June 2014 from website:
http://www.axis.com/files/whitethesis/wp_ccd_cmos_40722_en_1010_lo.pdf
[17] 雷良煥，黃吉成，徐永珍，“後來居上的CMOS影像感測器”，物理雙月
刊32卷1期，2010年2月，pp.24-29.
[18] Y. Freund, R. E. Schapire, “A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting”, Journal of Computer and System Sciences, Vol. 55, No.1, 1997, pp. 119-139.
[19] 林良達， “基於車用影像之即時行人碰撞預警系統”，國立成功大學 碩士論文，民國一零二年。
[20] P. Viola, J. J. Michael, “Robust Real-Time Face Detection”, International Journal of Computer Vision, Vol. 57, No. 2, 2004, pp. 137-154.
[21] J. Mrovlje, D. Vrančić, “Distance Measuring Based on Stereoscopic Pictures”, the 9th International PhD Workshop on Systems and Control, Slovenia, Oct. 2008.
[22] 林可薇， “以HOG為基礎的AdaBoost方法做行人的頭部和肩部檢測”，國立清華大學 碩士論文，民國一百年。
[23] R. C. Gonzalez, Digital Image Processing, Upper Saddle River, N. J. Prentice Hall, 2002, ISBN 0-201-18075-8.
[24] G. Bradski, Learning OpenCV: Computer Vision in C++ with the OpenCV library, O'Reilly Media, 2013, ISBN 978-144-931-465-1.
[25] National Institute for Research in Computer Science and Control, INRIA Person Dataset, available in March 2014 from website:
http://pascal.inrialpes.fr/data/human/