Abstract
This paper shows a vision-based obstacle detection approach in an outdoor sidewalk environment. There is a major problem of applying single camera in outdoor navigation mission, that is the differentiation of various types of barriers and clutter pavement. To settle this issue, the property that pavement margins are sub-sampled while barrier margins are oversampled when the original image is mapped to the virtual plane of the top view. Morphology filters are applied to strengthen barrier margins as margin-blobs with greater size, while sparse margins from pavement are screened. On basis of the recognized barriers, secure walking areas are predicted by tracking a polar margin-blob histogram. The test of algorithm is made in various sidewalk scenes with complicated pavements with confirmed potency.
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