thiagortk

Computer Vision Engineer / Researcher

Fysight / LunaFlorianópolis, SC, Brazil

Pinned Repositories

Low-cost-Passive-camera-and-Active-LIDAR-Vision-for-Obstacle-Depth
Example of disparity map created by stereo correspondence through two images and a point cloud map created by LIDAR data values (distances measures).
Language:C++3 3 01
maskRCNN-DisparityMap-OpicalFlow
Using Disparity Map and Optical Flow info to extract features from the detected objects from maskRCNN.
Language:Python5 3 02
Road-Surface-Classification
In emerging countries it’s common to find unpaved roads or roads with no maintenance. Unpaved or damaged roads also impact in higher fuel costs and vehicle maintenance. This kind of analysis can be useful for both road maintenance departments as well as for autonomous vehicle navigation systems to verify potential critical points. The road type and quality classifier was done through a simple Convolutional Neural Network with few steps.
Language:Python37 2 117
Road-surface-detection-and-differentiation-considering-surface-damages
Semantic Segmentation in road surfaces, considering different pattern like asphalt, unpaved, potholes, etc.
Language:Jupyter Notebook52 5 428
Stereo-Vision
C++ example codes for camera calibration, rectification and to build disparity maps
Language:C++52 3 019
thiagortk
My profile README
0 2 00

thiagortk/Road-surface-detection-and-differentiation-considering-surface-damages
Semantic Segmentation in road surfaces, considering different pattern like asphalt, unpaved, potholes, etc.
Language:Jupyter Notebook52 5 428
thiagortk/Stereo-Vision
C++ example codes for camera calibration, rectification and to build disparity maps
Language:C++52 3 019
thiagortk/Road-Surface-Classification
In emerging countries it’s common to find unpaved roads or roads with no maintenance. Unpaved or damaged roads also impact in higher fuel costs and vehicle maintenance. This kind of analysis can be useful for both road maintenance departments as well as for autonomous vehicle navigation systems to verify potential critical points. The road type and quality classifier was done through a simple Convolutional Neural Network with few steps.
Language:Python37 2 117
thiagortk/maskRCNN-DisparityMap-OpicalFlow
Using Disparity Map and Optical Flow info to extract features from the detected objects from maskRCNN.
Language:Python5 3 02
thiagortk/Low-cost-Passive-camera-and-Active-LIDAR-Vision-for-Obstacle-Depth
Example of disparity map created by stereo correspondence through two images and a point cloud map created by LIDAR data values (distances measures).
Language:C++3 3 01
thiagortk/thiagortk
My profile README
0 2 00