1. A method of hand position detection, comprising: extracting, via an image processing module of an electronics device, a feature set associated with hand gesture detection and hand pose inference from at least one input image, the feature set including extracted image pyramids; inferring a hand pose type using a trained multiclass support vector machine (SVM); extracting pixel intensity or displacement features and scale invariant feature transforms (SIFT) features using the generated image pyramids; and approximating the hand pose using inverse kinematics (IK) optimization.
1. A method of hand position detection, comprising: extracting, via an image processing module of an electronics device, a feature set associated with hand gesture detection and hand pose inference from at least one input image, the feature set including extracted image pyramids; inferring a hand pose type using a trained multiclass support vector machine (SVM); extracting pixel intensity or displacement features and scale invariant feature transforms (SIFT) features using the generated image pyramids; and approximating the hand pose using inverse kinematics (IK) optimization. 3. The method according to claim 1 , further comprising applying a cascade filter in association with extracting a pixel intensity or displacement features and the SIFT features from the generated image pyramids.