基於行人影像計算垂直線消失點做人物定位

Calculation of vanishing point of vertical lines using pedestrian images for People Localization

李宗軒(Tsung-Hsuan Li)

指導教授 ： 莊仁輝

國立交通大學/資訊學院/多媒體工程研究所/碩士(2014年)

https://doi.org/10.6842/NCTU.2014.00743

摘要

人物定位技術在視訊監控與數位生活方面有廣泛的應用，因此必須提升效率才能處理日益增加的需求。先前基於消失點之線取樣的多攝影機定位方法固然可以提供即時且正確的人物定位成果，然而該方法必須先取得垂直線消失點的座標才能夠進行取樣的動作，所以常見的方法是在場景中設置與基準平面(地平面)垂直的校正杆，再透過拍攝校正杆影像並計算其交點來取得消失點。但使用校正杆的方法有時會受到場地所限制而難以實施，例如行人穿越道。為此，本篇論文提出基於行人影像的演算法，從前景(人物)區域找出虛擬校正杆，以避免設置實際校正杆的困難，增加使用基於消失點之線取樣的方法的可行性。

關鍵字

行人影像 ； 人物定位 ； 垂直線消失點

並列摘要

People localization is prevailing in applications of video surveillance and digital life. Due to the ever-increasing demand, it is necessary to improve its efficiency. While vanishing point-based line sampling is used to develop real-time multi-camera people localization methods, such methods need to obtain vanishing point of vertical lines for line sampling. Conventionally, the vanishing point is estimated by intersection of calibration pillars that are perpendicular to the ground plane. However, it may not be suitable to set calibration pillars in crowded scenes like street crossing. Accordingly, a pedestrian image-based algorithm is proposed in this paper which focuses on finding virtual calibration pillars from foreground (human) regions to avoid the difficulty of setting calibration pillars, making vanishing point-based line sampling methods easy-to-use.

並列關鍵字

pedestrian images ； people localization ； vanishing point of vertical lines

參考文獻

[9] Ping-Sung Liao, Tse-Sheng Chen and Pau-Choo Chung, “A Fast Algorithm for Multilevel Thresholding,” Journal of Information Science and Engineering, vol. 17, no. 5, pp. 713-727, 2001.

[3] Kuo-Hua Lo and Jen-Hui Chuang, “Vanishing point-based line sampling for efficient axis-based people localization,” IEEE Int. Conf. on Image Processing, 2011.

[4] Nils Krahnstoever and Paulo R. S. Mendonca, “Bayesian Autocalibration for Surveillance,” IEEE Int. Conf. on Computer Vision, 2005.

[5] Branislav Micusik and Tomas Pajdla, “Simultaneous surveillance camera calibration and foot-head homology,” IEEE Conf. Computer Vision and Pattern Recognition, 2010.

[6] Jon Louis Bentley, “Multidimensional binary search trees used for associative searching,” Communications of the ACM, 1975.