Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fast and Accurate Algorithm for Eye Localization for Gaze Tracking in
  Low Resolution Images   Iris centre localization in low-resolution visible images is a challenging
problem in computer vision community due to noise, shadows, occlusions, pose
variations, eye blinks, etc. This paper proposes an efficient method for
determining iris centre in low-resolution images in the visible spectrum. Even
low-cost consumer-grade webcams can be used for gaze tracking without any
additional hardware. A two-stage algorithm is proposed for iris centre
localization. The proposed method uses geometrical characteristics of the eye.
In the first stage, a fast convolution based approach is used for obtaining the
coarse location of iris centre (IC). The IC location is further refined in the
second stage using boundary tracing and ellipse fitting. The algorithm has been
evaluated in public databases like BioID, Gi4E and is found to outperform the
state of the art methods.

30
The categories of this paper are: q-alg
23
The categories of this paper are: solv-int
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
2
The categories of this paper are: math
19
The categories of this paper are: eess
32
The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol