Complete 3D mapping of indoor construction scenes using images and videos is a challenging task. It requires all workspaces to be continuously captured to enable complete modeling of the rapidly changing environments. Nonetheless, manually mapping an entire workspace on a daily basis is time-consuming. Also, at building sites, guaranteeing complete 3D mapping require carefully accounting for transitions in hallways for moving the camera from one workspace to another. To address these challenges, this paper presents a new method together with a workflow that optimizes data capture and enables complete 3D modeling. Using daily images taken, a pipeline of structure from motion coupled with multi-view dense reconstruction algorithms enables complete 3D modeling in each workspace. Walkthrough videos are then recorded weekly and are provided as input to a variant of a SLAM algorithm to tie in locally reconstructed workspaces in 3D. This enables project teams to capture images of each workspace-where work is continuously changing-at a high frequency (e.g., daily) and continuously produce dense 3D models. It also leverages a video capture of the entire workspace on a low frequency (e.g., weekly) to tie in locally produced dense 3D models. Preliminary results from a project site show that by decentralizing the image capture of each workspace to the trades as part of their required daily field reporting, and rapidly videotaping all work locations by a site engineer as part of a weekly walkthrough, the entirety of an indoor phase of construction project can be mapped in 3D. The specifics of the method and the benefits and challenges of the implementation workflow are discussed in detail.