Model based three dimensional hand posture recognition for hand tracking



This study focuses on model based hand posture recognition, which is the acquisition of the static hand pose information. Here, we have applied geometric modeling with a simple 3D hand model constructed with basic geometric shapes namely, cylinders and spheres. Our similarity measure is the non–overlapping area of silhouette of the model and the images acquired from the camera. This measure is optimized so as to estimate the best matches using two search methods, the genetic algorithm and the downhill simplex method.


Ayse Naz Erkan