SEMANTIC INTERPRETATION OF 3-D STEREO DATA: FINDING THE MAIN STRUCTURES

We are interested in the semantic interpretation of 3-D data obtained by a stereovision algorithm, in the context of indoor scenes. This paper presents a high level process built to find the main plane structures of the scene and to label them with a semantic description. This process is made up of three stages: first, the sorting and enhancement of the input data (3-D segments), second, the generation of affine planes from the sorted 3-D segments and finally, the semantic description of these planes by a classification expert system using the interpreter CLASSIC. This process has been tested on various stereo images and the quality of the results, in robustness and accuracy, are quite good. The advantages of using a knowledge based system are discussed.