Recent Advances on 2D and 3D Change Detection in Urban Environments from Remote Sensing Data - Computational Approaches for Urban Environments - page 249

Fig. 10.5 Supervised 2D building detection based on data classification algorithms. Upper row :
A Pleiades image acquired in 2013 ( left ) and the result from a standard minimum distance
classification algorithm (showing only classes related to buildings). The quantitative evaluation
reported a low detection overall quality of 62 %. Middle row : The result from a standard maximum
likelihood classification algorithm with an overall detection rate of 67 % ( left ). A SVM classifier
scores higher with an overall detection quality of 74 % ( right ). Bottom row : The detected buildings,
after post-classification processing in the SVM output, are labeled and shown with different colors
( left ). The detected buildings overlaid on the raw Pleiades image ( right )