Authors:
Amin Dadgar
and
Guido Brunnett
Affiliation:
Computer Science, Chemnitz University of Technology, Straße der Nationen 62, 09111, Chemnitz, Germany
Keyword(s):
One-D Finger Pose-Descriptor, Distance-Based Descriptor, Anatomy-Based Dimensionality Reduction, Temporal a-Priori, Hand Posture Estimation, Single RGB Camera, Virtual Hand Models, Computer Vision.
Abstract:
We claim there is a simple measure to characterize all postures of every finger in human hands, each with a single and unique value. To that, we illustrate the sum of distances of fingers’ (movable) joints/nodes (or of the finger’s tip) to a locally fixed reference point on that hand (e.g., wrist joint) equals a unique value for each finger’s posture. We support our hypothesis by presenting numerical justification based on the kinematic skeleton of a human hand for four fingers and by providing evidence on two virtual hand models (which closely resemble the structure of human hands) for thumbs. The employment of this descriptor reduces the dimensionality of the finger’s space from 16 to 5 (e.g., one degree of freedom for each finger). To demonstrate the advantages of employing this measure for finger pose estimation, we utilize it as a temporal a-priori in the analysis-by-synthesis framework to constrain the posture space in searching and estimating the optimum pose of fingers more e
fficiently. In a set of experiments, we show the benefits of employing this descriptor in time complexity, latency, and accuracy of the pose estimation of our virtual hand.
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