农业工程学报
農業工程學報
농업공정학보
2014年
9期
168-175
,共8页
胡少军%耿楠%张志毅%杨沛%何东健
鬍少軍%耿楠%張誌毅%楊沛%何東健
호소군%경남%장지의%양패%하동건
树%模型%三维%交互式%稀疏图像
樹%模型%三維%交互式%稀疏圖像
수%모형%삼유%교호식%희소도상
trees%models%three-dimensional%interactive%sparse image
真实环境中树的三维重建可在虚拟现实、景观设计及农林业应用方面发挥重要作用,为解决真实环境中树的三维重建问题,该文提出一种基于稀疏图像的交互式建模方法。在自然环境下采集2幅相差90°的树图像及对应4~7幅中间图像,采用交互式编辑方法在夹角相差90°的1幅图像上获取各级树枝二维投影位置及粗度信息,再通过中间图像找到各级树枝在另一幅图像上的匹配树枝,并交互式调整树枝位置信息,然后进行透视校正,生成树枝三维几何模型,最后根据叶序规则添加树叶完成重建。通过对苹果树、樱桃树和枫树的重建结果表明,该方法交互性好,对图像拍摄数量与角度要求不高,重建时间在55~125 min 之间,且能较好保持树的拓扑结构,可为虚拟植物建模、虚拟修剪试验和植物拓扑结构分析等提供参考。
真實環境中樹的三維重建可在虛擬現實、景觀設計及農林業應用方麵髮揮重要作用,為解決真實環境中樹的三維重建問題,該文提齣一種基于稀疏圖像的交互式建模方法。在自然環境下採集2幅相差90°的樹圖像及對應4~7幅中間圖像,採用交互式編輯方法在夾角相差90°的1幅圖像上穫取各級樹枝二維投影位置及粗度信息,再通過中間圖像找到各級樹枝在另一幅圖像上的匹配樹枝,併交互式調整樹枝位置信息,然後進行透視校正,生成樹枝三維幾何模型,最後根據葉序規則添加樹葉完成重建。通過對蘋果樹、櫻桃樹和楓樹的重建結果錶明,該方法交互性好,對圖像拍攝數量與角度要求不高,重建時間在55~125 min 之間,且能較好保持樹的拓撲結構,可為虛擬植物建模、虛擬脩剪試驗和植物拓撲結構分析等提供參攷。
진실배경중수적삼유중건가재허의현실、경관설계급농임업응용방면발휘중요작용,위해결진실배경중수적삼유중건문제,해문제출일충기우희소도상적교호식건모방법。재자연배경하채집2폭상차90°적수도상급대응4~7폭중간도상,채용교호식편집방법재협각상차90°적1폭도상상획취각급수지이유투영위치급조도신식,재통과중간도상조도각급수지재령일폭도상상적필배수지,병교호식조정수지위치신식,연후진행투시교정,생성수지삼유궤하모형,최후근거협서규칙첨가수협완성중건。통과대평과수、앵도수화풍수적중건결과표명,해방법교호성호,대도상박섭수량여각도요구불고,중건시간재55~125 min 지간,차능교호보지수적탁복결구,가위허의식물건모、허의수전시험화식물탁복결구분석등제공삼고。
The creation of realistic outdoor trees is a challenging problem in the area of modeling natural phenomenon because trees have complex geometric structures. Currently, there are two major methods to achieve this goal. One approach models trees from image sequences. This approach requires more than 16 images and wide view angles to reconstruct tree point clouds and camera pose, and the reconstruction process is not easily implemented for non-expert users because of some complex computer vision techniques. The other approach uses a laser range scanner to acquire a point cloud for modeling trees. However, we need expensive hardware to obtain the point cloud. Furthermore, the background segmentation, the hole filling and the registration process of a point cloud is very cumbersome. In this paper, we present a low cost interactive modeling method to reconstruct real-world trees from sparse images. Our method has the advantage of preserving the branch structures of real trees with few images and limited viewing angle. Based on two input photographs taken from different views with the coverage of 90 degrees and 4 to 7 in-between photographs, we developed an interactive editing system to extract the node positions, the thickness of branches and the tree hierarchy from the front view image. The interactive editing system consists of branch (or node) drawing and modifying, branch (or node) inserting and deleting, thickness modifying, Hermite spline interpolation and tree hierarchy reconstruction parts. Next, we chose main branches as references, and interactively matched the corresponding branches from the side view image by making use of the in-between images. Then, we adapted the node positions using the editing system to obtain the depth information for each branch. By combining the extracted two dimensional node positions and the thickness of branch from the front view and the depth information from the side view, we drew the three dimensional tree using generalized cylinders. However, the reconstructed tree model showed distortion where the branches in the distance appeared smaller and the branches at close range appeared larger compared with the branches in the photograph. It can be explained by the double perspective projection phenomenon where the real-world objects have been transformed twice through taking photographs and through perspective transformation in OpenGL. We propose a perspective calibration method to avoid the distortion of reconstructed tree models. Leaves are difficult to be identified from images even by the interactive method. Thus, we designed a leaf arrangement algorithm and added leaves to each branch according to leaf phyllotaxis. Finally, we demonstrated the realistic reconstruction of a variety of tree species including apple trees, cherry trees and maple trees. The number of nodes of the reconstructed trees ranges from 736 to 1250, and the average reconstruction time is around 80 minutes for a medium scale tree. The result showed that our method is effective to model real world trees having clear branches and sparse leaves.