Sparse Features for Finger Detection

Abstract

The use of hand as direct input device evolved with the development of Natural User Interfaces (NUI). Touch screens are well integrated in our daily life and the new challenge is to implement interfaces which involve no direct contact. This paper presents such a solution implemented within the framework of sparse techniques. The feature vectors representing key distances and angles are extracted and used to detect fingers. The experimental results have demonstrated that this technique is able to obtain an error rate about 5% in finger detection.