【導(dǎo)讀】本文在結(jié)合地面激光掃描和近景攝影測(cè)量文物古跡文件的潛力進(jìn)行了討論。的幾何模型，一體化的目的是支持在歷史場(chǎng)景中如邊緣和縫隙的線性特性的視覺(jué)質(zhì)量。所有表面特征的輪廓，即使他們?cè)诂F(xiàn)實(shí)中都有清晰的輪廓。為此目的一個(gè)基于圖像數(shù)據(jù)的集成分割過(guò)程將支持對(duì)象的幾何信息從激光數(shù)。該方法適用于基于圖像的半自動(dòng)化技術(shù)以填補(bǔ)激光掃描數(shù)據(jù)的空白，并添加新的。細(xì)節(jié)，這就要求建立現(xiàn)場(chǎng)體積更現(xiàn)實(shí)的感知。實(shí)驗(yàn)的調(diào)查與實(shí)施是基于從艾爾卡茲尼寶庫(kù)獲。得的數(shù)據(jù)，一個(gè)在約旦佩特拉著名的紀(jì)念碑。即旅游的目的是為學(xué)生和研究。人員提供教育資源。進(jìn)行數(shù)字圖像采集現(xiàn)在是可行的。根據(jù)反射的光脈沖的運(yùn)行時(shí)數(shù)以百萬(wàn)計(jì)的三維點(diǎn)。了我國(guó)模范特征提取方法用于艾爾卡茲尼寶庫(kù)左門的混合動(dòng)力系統(tǒng)。之后一個(gè)旅客進(jìn)入佩特拉，從山上一兩公里令人。艾爾卡茲尼寶庫(kù)正面是高40米,保存相當(dāng)完好,可能是因?yàn)樗拿荛]空間保護(hù)它。選擇的觀測(cè)點(diǎn)位置的問(wèn)題作為調(diào)查這

　　

【正文】 ith initial values of the exterior orientation parameters is implemented. The extraction of straight edges from laser scanner data is simplified, if the required line is defined by two intersecting planar surfaces as it is demonstrated in figure 6. The corresponding edges in the digital image can be extracted interactively or semiautomatically based on edge segmentation. At least three corresponding straight lines are required to obtain a unique solution for the spatial resection. Distance Image Generation After the camera coordinates and orientation parameters are registered in the laser scanner coordinate system, the collinearity equations are applied to generate a distance image based on the available point clouds. For our exemplary scene, the point cloud was collected from a close viewpoint resulting in 1 cm average resolution. The distance images were generated with the same number of pixels of the corresponding images (1536x2304 pixels). For the left door of AlKhasneh, three distance images were generated for the three images available from different camera stations. Figure 7 depicts one of these distance images projected on Figure 7. The distance image of the left door projected on the corresponding image. Figure 8. 3D features extracted for the left door of AlKhasneh, the inner edge of the column is added from image based measurements. the corresponding image. Image Segmentation The segmentation process is used to automatically extract the 2D coordinates of the linear features from three different digital images. For this purpose, an edge detection based on the Lanser filter has been applied on the 3 imagery images. The third dimension of the segmented outlines is provided from the distance images. Figure 8, depicts the final 3D features extracted for the left door of AlKhasneh. It can be seen that the data contains all of the edges and linear surface features in a clearly outlines. In total the featurebased representation contains thousand points, whereas the original point cloud of the same portion has million points. Occluded Features from Image Based Measurement It can be seen from the 3D features presented in figure 5 that due to the position of the laser scanner, the inner edge of the right column of the door has no data. The occluded edge can be added based on semiautomatic evaluation of digital imagery to have a plete data set for the scene. In our approach, the 3D coordinates of initial points were extracted manually. Then an automatic stereo matching has been applied for closely spaced images to add more points on the edge. For matching within the segmented parts of the edge epipolar constraint is used. The occluded edge is added to the 3D features as it can be shown in right part of figure 8. 4 SUMMARY AND CONCLUSION The work described in this paper was developed as a part of an ongoing project, which aims to underline the necessity to integrate image based measurements and laser scanner techniques in order to optimize the geometric accuracy and the visual quality of 3D data capture for historical scenes. In our approach, the segmentation process is used as an intermediate step to extract information on edges and linear surface features, whereas the 3D information of theses details is provided from the laser scanner data. By the bination of both data sources, the shape of 3D features can be determined accurately, since the interpretation of point clouds and meshed models is improved using the available images. Finally, the approach applies semiautomated image based feature extraction. These features can be added to data from laser scanning in order to generate a more realistic perception of the plete scene. 5. ACKNOWLEDGEMENTS Special thanks to the Hashemite University of Jordan and Petra Region Authority for support during the data collection. 6. REFERENCES Boehler, W., Marbs, A., 2020. 3D scanning instruments. ISPRS/CIPA International Workshop on Scanning for Cultural Heritage Recording, Corfu, Greece, . Debevec, E., 1996. Modelling and Rendering Architecture from Photographs. . Thesis, University of California at Berkeley. ElHakim, S., Beraldin, A., Picard, M., 2020. Detailed 3D reconstruction of monuments using multiple techniques. ISPRS/CIPA International Workshop on Scanning for Cultural Heritage Recording, Corfu, Greece, . Gruen, A., Remondino, F., Zhang, L., 2020. Reconstruction of the great Buddha of bamiyan, Afghanistan. International Archives of Photogrammetry and Remote Sensing, Vol. XXXIV, part 5, Corfu, Greece, pp. 363368. Klinec, D., Fritsch, D., 2020. Towards pedestrian navigation and orientation. Proceedings of the 7th South East Asian Survey Congress: SEASC39。03, Hong Kong, November 37. Sedlaczek, B., 2020. Petra, Art and Legend. MP Graphic Formula, Roma, Italy, .