Alexander Medeiros
Adv. Artif. Intell. Mach. Learn., 3 (4):1787-1799
1. Alexander Medeiros: FINRA
DOI: 10.54364/AAIML.2023.11103
Article History: Received on: 24-Oct-23, Accepted on: 21-Dec-23, Published on: 28-Dec-23
Corresponding Author: Alexander Medeiros
Email: ajmed13@gmail.com
Citation: Alexander J. Medeiros, et al. Handsight: DeCAF & Improved Fisher Vectors to Classify Clothing Color and Texture With a Finger-Mounted Camera. Advances in Artificial Intelligence and Machine Learning. 2023;3(4):103.
We demonstrate the use of DeCAF and Improved Fisher Vector image features for clothing texture classification, with a focus on aiding visually impaired individuals in selecting their attire. Choosing clothes based on color and texture is a daily problem for visually impaired individuals. This work is a preliminary attempt to alleviate the problem using a finger-mounted camera and state-of-the-art classification algorithms to identify clothing textures. In evaluating our solution, we used a NanEyeGS camera, small enough to mount on a finger, to collect 520 close-up images across 29 garments, referred to as the HandSight Color Texture Dataset (HCTD). Secondly, we contribute evaluations of these state-of-the-art recognition algorithms applied to our dataset - achieving an accuracy exceeding 95%. Throughout this article, we review prior research, evaluate our current solution, and outline future project directions.