bundle block adjustment with 3d natural cubic splines

[60], Ebner and Ohlhof(1994) [16], Ackerman and Tsingas(1994) [1], Haala and Vosselman(1992)[24], Drewniok and Rohr(1996, 1997) [14][15], Zahran(1997) [77] andSchenk(1998) [56]. However, point-based photogrammetry based on the manual measurementand identification of interest points is not established successfully in theautonomous environment of digital photogrammetry but the labor-intensive interpretationsince it has the limitation of occlusion, ambiguity and semantic information inview of robust and suitable automation.Since point features do not provide explicit geometric information, the geometricalknowledge is achieved by perceptual organization [55] [23] [10] [8]. Perceptualorganization derives features and structures from imagery without prior knowledgeof geometric, spectral or radiometric properties of features and is a required stepfor object recognition. Perceptual organization is an intermediate level process forvarious vision tasks such as target-to-background discrimination, object recognition,target cueing, motion-based grouping, surface reconstruction, image interpretation,and change detection. Since objects can not be distinguished by one gray level pixel,an image must be investigated entirely to obtain perceptual information. Most recentresearches related to perceptual organization are the 2D image implementationat signal, primitive and structural levels.Generally grouping or segmentation has the same meaning with perceptual organizationin computer vision. Segmentation in computer vision is typically divided intotwo approaches, model-based method (top-down approach) and data-based method(bottom-up approach), and many researchers have employed edges and regions insegmentation.In edge-based approaches, edges are liked to general forms of linearfeatures without discontinuities and in region-based approaches iterative region13