Joint Depth and Color Camera Calibration with Distortion Correction
By D. Herrera C., Juho Kannala, Janne Heikkilä. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012
364 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/194bfb3ba7a4865b7afd98ebfd80823d245e5f18
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Vladlen Koltun
- Marc Pollefeys
- Qian-Yi Zhou
- Torsten Sattler
- Stephen D. Miller
- Thomas Schöps
- Andreas Kolb
- Jean-Luc Dugelay
In Computer Vision and Pattern Recognition
- Vladlen Koltun
- Luc Van Gool
- Marc Pollefeys
- Dacheng Tao
- Jitendra Malik
- In-So Kweon
- Ming-Hsuan Yang
- Xiaogang Wang
Citations in the corpus
- Evaluating and Improving the Depth Accuracy of Kinect for Windows v2 (2015, methodology): “separately proposed algorithms to calibrate the color-depth camera pair [16], [17].”
- Kinect range sensing: Structured-light versus Time-of-Flight Kinect (2015, background): “Thus, even though we refer to characteristics of the specific range measurement techniques, the resulting effects may not only relate to the sensor hardware, i.e. to the measurement principle as such, but also to the post-processing integrated into the cameras”
- Describing Trajectory of Surface Patch for Human Action Recognition on RGB and Depth Videos (2015, background): “The main contribution is that we propose a new feature for action representation in RGB-D videos which has the advantages of trajectories and local spatial-temporal features by making full advantages of RGB and depth information.”
- KinectFaceDB: A Kinect Database for Face Recognition (2014, background): “Some previous works made additional efforts to calibrate the intrinsic and extrinsic parameters of the RGB camera based on an extra RGB camera [31] or the embedded IR camera [32].”
- BAD SLAM: Bundle Adjusted Direct RGB-D SLAM (2019, methodology): “We use the depth offset model from [26], which relates true inverse depths dtrue to distorted inverse depths ddist for every pixel (x, y) as”
- KAIST Multi-Spectral Day/Night Data Set for Autonomous and Assisted Driving (2018, background): “(b) Herrera and Heikkila [15].”
- An overview of depth cameras and range scanners based on time-of-flight technologies (2016, methodology): “A related method, which does include distortion correction, has been demonstrated for Kinect v1 [34].”
- Elastic Fragments for Dense Scene Reconstruction (2013, background): “A related source of difficulty is the substantial lowfrequency distortion present in range images produced by consumer-grade sensors [27, 11, 8].”