The invention discloses a multi-starting-point incremental three-dimensional reconstruction method based on large-scale disordered images. The method comprises the steps of performing image matching, constructing a matching relationship chart, selecting a reconstruction starting point, detecting an edge, performing multi-starting-point three-dimensional reconstruction and splicing a submodel. By means of a clustering strategy and an iteration drift strategy, an image pair which is suitable as starting points is adaptively selected from a disordered image set and reconstruction is performed simultaneously; before reconstruction, determining an optimal reconstruction sub-process of each image according to a layered shortest path first algorithm, and determining a reconstruction boundary; and obtaining a whole three-dimensional reconstruction model according to sub-models obtained in different sub-processes and splicing the common parts contained in the sub-models. The three-dimensional reconstruction method according to the invention has advantages of settling a problem of suspension in reconstruction process when a current scene comprises a plurality of non-overlapped parts, obtaining a whole three-dimensional model which is covered by the image set, preventing three-dimensional structure error caused by matching and transmission of error images, realizing parallel processing in reconstruction sub-process, and improving image reconstruction efficiency.