Name
Title | ||
|---|---|---|
A Wearable Face Recognition System Built into a Smartwatch and the Visually Impaired User. |
Abstract | ||
|---|---|---|
Practitioners usually expect that real-time computer vision systems such as face recognition systems willrequire hardware components with high processing power. In this paper, we present a concept to show thatit is technically possible to develop a simple real-time face recognition system in a wearable device withlow processing power ??? in this case an assistive device for the visually impaired. Our platform of choicehere is the first generation Samsung Galaxy Gear smartwatch. Running solely in the watch, without pairingto a phone or tablet, the system detects a face in the image captured by the camera, and then performs facerecognition (on a limited dictionary), emitting an audio feedback that either identifies the recognized personor indicates that s/he is unknown. For the face recognition approach we use a variation of the K-NNalgorithm which accomplished the task with high accuracy rates. This paper presents the proposed systemand preliminary results on its evaluation. |
Year | Venue | Field |
|---|---|---|
2015 | ICEIS (3-1) | Computer vision,Facial recognition system,Wearable computer,Computer science,Audio feedback,Phone,Artificial intelligence,Smartwatch |
DocType | Citations | PageRank |
Conference | 3 | 0.39 |
References | Authors | |
20 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laurindo de Sousa Britto Neto | 1 | 16 | 2.08 |
| Vanessa Regina Margareth Lima Maike | 2 | 19 | 4.51 |
| Fernando Luiz Koch | 3 | 141 | 11.48 |
| Maria Cecília Calani Baranauskas | 4 | 339 | 63.84 |
| Anderson Rocha | 5 | 913 | 69.11 |
| Siome Goldenstein | 6 | 618 | 47.43 |