Combining Deep Learning with Geometric Features for Image based Localization in the Gastrointestinal Tract

by   Jingwei Song, et al.

Tracking monocular colonoscope in the Gastrointestinal tract (GI) is a challenging problem as the images suffer from deformation, blurred textures, significant changes in appearance. They greatly restrict the tracking ability of conventional geometry based methods. Even though Deep Learning (DL) can overcome these issues, limited labeling data is a roadblock to state-of-art DL method. Considering these, we propose a novel approach to combine DL method with traditional feature based approach to achieve better localization with small training data. Our method fully exploits the best of both worlds by introducing a Siamese network structure to perform few-shot classification to the closest zone in the segmented training image set. The classified label is further adopted to initialize the pose of scope. To fully use the training dataset, a pre-generated triangulated map points within the zone in the training set are registered with observation and contribute to estimating the optimal pose of the test image. The proposed hybrid method is extensively tested and compared with existing methods, and the result shows significant improvement over traditional geometric based or DL based localization. The accuracy is improved by 28.94 to state-of-art method.



There are no comments yet.


page 2

page 7


Fusing Convolutional Neural Network and Geometric Constraint for Image-based Indoor Localization

This paper proposes a new image-based localization framework that explic...

GANerated Hands for Real-time 3D Hand Tracking from Monocular RGB

We address the highly challenging problem of real-time 3D hand tracking ...

Three dimensional Deep Learning approach for remote sensing image classification

Recently, a variety of approaches has been enriching the field of Remote...

Deep Learning for Visual Tracking: A Comprehensive Survey

Visual target tracking is one of the most sought-after yet challenging r...

Deep Hybrid Real and Synthetic Training for Intrinsic Decomposition

Intrinsic image decomposition is the process of separating the reflectan...

Towards Sustainable Deep Learning for Wireless Fingerprinting Localization

Location based services, already popular with end users, are now inevita...

Deep Learning Based Multi-Label Text Classification of UNGA Resolutions

The main goal of this research is to produce a useful software for Unite...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.