Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian dense inverse searching algorithm for real-time stereo matching
  in minimally invasive surgery   This paper reports a CPU-level real-time stereo matching method for surgical
images (10 Hz on 640 * 480 image with a single core of i5-9400). The proposed
method is built on the fast ''dense inverse searching'' algorithm, which
estimates the disparity of the stereo images. The overlapping image patches
(arbitrary squared image segment) from the images at different scales are
aligned based on the photometric consistency presumption. We propose a Bayesian
framework to evaluate the probability of the optimized patch disparity at
different scales. Moreover, we introduce a spatial Gaussian mixed probability
distribution to address the pixel-wise probability within the patch. In-vivo
and synthetic experiments show that our method can handle ambiguities resulted
from the textureless surfaces and the photometric inconsistency caused by the
Lambertian reflectance. Our Bayesian method correctly balances the probability
of the patch for stereo images at different scales. Experiments indicate that
the estimated depth has higher accuracy and fewer outliers than the baseline
methods in the surgical scenario.

11
The categories of this paper are: hep-lat
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas