Automatic Streaming Segmentation of Stereo Video Using Bilateral Space

10/10/2017
by   Wenjing Ke, et al.
0

In this paper, we take advantage of binocular camera and propose an unsupervised algorithm based on semi-supervised segmentation algorithm and extracting foreground part efficiently. We creatively embed depth information into bilateral grid in the graph cut model and achieve considerable segmenting accuracy in the case of no user input. The experi- ment approves the high precision, time efficiency of our algorithm and its adaptation to complex natural scenario which is significant for practical application.

READ FULL TEXT

page 5

page 9

page 11

research
12/26/2022

Semi-Supervised Domain Adaptation for Semantic Segmentation of Roads from Satellite Images

This paper presents the preliminary findings of a semi-supervised segmen...
research
05/18/2019

Semi-Supervised Monocular Depth Estimation with Left-Right Consistency Using Deep Neural Network

There has been tremendous research progress in estimating the depth of a...
research
04/09/2018

Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning

This paper tackles the problem of video object segmentation, given some ...
research
01/21/2004

Better Foreground Segmentation Through Graph Cuts

For many tracking and surveillance applications, background subtraction ...
research
09/29/2016

Modelling depth for nonparametric foreground segmentation using RGBD devices

The problem of detecting changes in a scene and segmenting the foregroun...
research
09/03/2016

Towards Segmenting Consumer Stereo Videos: Benchmark, Baselines and Ensembles

Are we ready to segment consumer stereo videos? The amount of this data ...
research
11/09/2016

Semi-Supervised Recognition of the Diploglossus Millepunctatus Lizard Species using Artificial Vision Algorithms

Animal biometrics is an important requirement for monitoring and conserv...

Please sign up or login with your details

Forgot password? Click here to reset