# A scene perception system for visually impaired based on object detection and classification using multi-modal DCNN

Source: [A scene perception system for visually impaired based on object detection and classification using multi-modal DCNN](<https://www.sota2.com/research/paper/68fa65a71e209131cea0ba16>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T21:32:37.817Z

Authors: Baljit Kaur, Jhilik Bhattacharya

Published: 2018-05-22T18:02:08.000Z

## Abstract

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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1805.08798>)

[PDF](<https://arxiv.org/pdf/1805.08798.pdf>)