Nearest Prime Simplicial Complex for Object Recognition

Details Nearest Prime Simplicial Complex for Object Recognition Nearest Prime Simplicial Complex for Object Recognition

2011-06-06

arxiv.org/abs/1106.0987v1

Computer Science

Learning

16pages, 6 figures

Scientific paper

The structure representation of data distribution plays an important role in understanding the underlying mechanism of generating data. In this paper, we propose nearest prime simplicial complex approaches (NSC) by utilizing persistent homology to capture such structures. Assuming that each class is represented with a prime simplicial complex, we classify unlabeled samples based on the nearest projection distances from the samples to the simplicial complexes. We also extend the extrapolation ability of these complexes with a projection constraint term. Experiments in simulated and practical datasets indicate that compared with several published algorithms, the proposed NSC approaches achieve promising performance without losing the structure representation.

Affiliated with

Also associated with

No associations

Rating

Nearest Prime Simplicial Complex for Object Recognition 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 Nearest Prime Simplicial Complex for Object Recognition, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Nearest Prime Simplicial Complex for Object Recognition will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-389269