Name: Allen Frank Cutinha
Type: User
Company: Panasonic - Senior Computer Vision software engineer
Bio: Tech-savvy software engineer in computer vision, who loves to draw, read, connect with others, and stay active.
Location: Frankfurt, Germany
Allen Frank Cutinha's Projects
Implements the Agglomerative Hierarchical Clustering algorithm.
ARCore Depth Lab is a set of Depth API samples that provides assets using depth for advanced geometry-aware features in AR interaction and rendering. (UIST 2020)
corner detection of calibration images
:books: List of awesome university courses for learning Computer Science!
:sunglasses: A curated list of robotics libraries and software
simple lambda handler to read and display json structure
The Kalibr visual-inertial calibration toolbox
A visual-inertial calibration library designed for rapid problem construction and debugging.
Utility for camera calibration
C++ implementation of camera models in SLAM, see https://blog.csdn.net/OKasy/article/details/90665534.
CamOdoCal: Automatic Intrinsic and Extrinsic Calibration of a Rig with Multiple Generic Cameras and Odometry
all possible projects form carND program
An easy to use ceres-solver port for Visual Studio on Windows, using Eigen for sparse linear algebra and Google glog for logging.
My C++ solutions to the Lessons section of Codility
I am trying to finish the lessons of the codility's training center
A complete computer science study plan to become a software engineer.
cpp_samples
Collaborative Collection of C++ Best Practices. This online resource is part of Jason Turner's collection of C++ Best Practices resources. See README.md for more information.
custom implemenattion on canny edge detection
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Code for the project Deep Drone Acrobatics.
Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)
Direct Sparse Odometry
ROS wrapper for dso
CVPRW 2021: How to calibrate your event camera
Code exercises for the SLAM course in 'Computer Vision, LiDAR processing, and Sensor Fusion for Autonomous Driving' lecture series
This is my version of the Fastest Pedestrian Detector in the West
Googletest - Google Testing and Mocking Framework