  This paper represents a cost-effective scene perception system aimed towards
visually impaired individual. We use an odroid system integrated with an USB
camera and USB laser that can be attached on the chest. The system classifies
the detected objects along with its distance from the user and provides a voice
output. Experimental results provided in this paper use outdoor traffic scenes.
The object detection and classification framework exploits a multi-modal fusion
based faster RCNN using motion, sharpening and blurring filters for efficient
feature representation.
