Damage assessment, change detection or geographical database update are traditionally performed by experts looking for objects in images, a task which is costly, time consuming and error prone. Automatic solutions for building verification are particularly welcome but suffer from illumination and perspective changes On the other hand, semi-automatic procedures intend to speed up image analysis while limiting human intervention to doubtful cases We present a semiautomatic approach to assess the presence of buildings in airborne images from geometrical and photometric cues. For each polygon of the vector database representing a building, a score is assigned, combining geometrical and photometric cues Geometrical cues relate to the proximity, parallelism and coverage of linear edge segments detected in the image while photometric factor measures shadow evidence based on intensity levels in the vicinity of the polygon The human operator interacts with this automatic scoring by setting a threshold to highlight buildings poorly assessed by image geometrical and photometric features After image inspection, the operator may decide to mark the polygon as changed or to update the database, depending on the application.
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