SUMMARY
Traditional photogrammetric activities such as orientation, triangulation, and objectspace reconstruction have been relying on distinct points in their underlyingoperations. With the evolution of digital photogrammetry, there has been atremendous interest in utilizing linear features in various photogrammetricactivities. This interest has been motivated by the fact that the extraction of linearfeatures from the image space is easier to automate than distinct points. On the otherhand, object space linear features can be directly derived form terrestrial MobileMapping Systems (MMS), GIS databases, and/or existing maps. Moreover,automatic matching of linear features, either within overlapping images or betweenimage and object space, is easier than that of distinct points. Finally, linear featurespossess more semantic information than distinct points since they most probablycorrespond to object boundaries. Such semantics can be automatically identified inimagery to facilitate higher-level tasks (e.g., surface reconstruction and objectrecognition). This paper summarizes the use of linear features, which might berepresented by analytical functions (e.g., straight-line segments) or irregular (freeform)shapes, in photogrammetric activities such as automatic space resection,photogrammetric triangulation, camera calibration, image matching, surfacereconstruction, image-to-image registration, and absolute orientation. Currentprogress, future expectations, and possible research directions are discussed as well.