FEATURE EVALUATION FOR BUILDING FACADE IMAGES – AN EMPIRICAL STUDY

FEATURE EVALUATION FOR BUILDING FACADE IMAGES – AN EMPIRICAL STUDY

Blog Article

The classification of building facade 30x24x24 wall cabinet images is a challenging problem that receives a great deal of attention in the photogrammetry community.Image classification is critically dependent on the features.In this paper, we perform an empirical feature evaluation task for building facade images.Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features.

We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features.We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object 392 cam kit classes building, car, door, pavement, road, sky, vegetation, and window.