Deciding of HMM parameters based on number of critical points for gesture recognition from motion capture data

Details Deciding of HMM parameters based on number of critical points for gesture recognition from motion capture data Deciding of HMM parameters based on number of critical points for gesture recognition from motion capture data

2011-10-28

arxiv.org/abs/1110.6287v1

Computer Science

Learning

Scientific paper

This paper presents a method of choosing number of states of a HMM based on number of critical points of the motion capture data. The choice of Hidden Markov Models(HMM) parameters is crucial for recognizer's performance as it is the first step of the training and cannot be corrected automatically within HMM. In this article we define predictor of number of states based on number of critical points of the sequence and test its effectiveness against sample data.

Affiliated with

Also associated with

No associations

Rating

Deciding of HMM parameters based on number of critical points for gesture recognition from motion capture data does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Deciding of HMM parameters based on number of critical points for gesture recognition from motion capture data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Deciding of HMM parameters based on number of critical points for gesture recognition from motion capture data will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-686004