Indoor mapping using planes extracted from noisy RGB-D sensors

By Tae-Kyeong Lee, Seungwook Lim, Seongsoo Lee, Shounan An, Se-Young Oh. 2012

62 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

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

1. Ling Shao
2. Jungong Han
3. Ziyun Cai
4. Kai Berger
5. Li Liu
6. Yi-Zhe Song

In Computer Vision and Pattern Recognition

1. Li Liu
2. Jungong Han
3. Ling Shao
4. Ziyun Cai
5. Kai Berger
6. Yi-Zhe Song
7. Jianbing Shen
8. Wenguan Wang

Citations in the corpus

• RGB-D datasets using microsoft kinect or similar sensors: a survey (2016, methodology): “Six research publications about evaluating ego-motion estimation and SLAM over TUM Benchmark dataset are [21, 38, 45, 84, 86, 87].”
• The role of RGB-D benchmark datasets: an overview (2013, background): “A tabular overview about the corresponding publications for each dataset can found in Table 1.”