Outdoor Situation Awareness

(This paper was accepted at the ICPRAM 2016.)

The goal of the proposed system is to increase the safety of users while they walk by recognizing their current context. The proposed system automatically detects the current outdoor context, e.g. traffic intersections, roadways, and sidewalks, and notifies the users of the results using auditory or vibration feedback. In order to automatically recognize the outdoor context, the proposed system is performed by three steps: preprocessing, feature extraction, and context recognition. First, it improves the image contrast while removing image noise, and then it extracts the color and texture descriptors. Next, each pixel is categorized as an intersection, sidewalk, or roadway using a support vector machine-based hierarchical classifier.

The key elements for context recognition are the boundary orientations between sidewalks and roadways: horizontally oriented boundaries are found in images corresponding to intersections and more vertically oriented boundaries are observed in images corresponding to sidewalks. Accordingly, the boundary should be first discriminated from other natural lines; then, these pixels should be classified. In the proposed method, such classifications are accomplished using a multi-scale classification.