Fast multiple objects detection and tracking fusing color camera and 3D LIDAR for intelligent vehicles

By Soonmin Hwang, Namil Kim, Yukyung Choi, Seokju Lee, In-So Kweon. 2016

41 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. Vinicius B. Cardoso
2. Thiago Oliveira-Santos
3. Raphael V. Carneiro
4. Pedro Azevedo
5. A. D. Souza
6. Kazuya Takeda
7. Alexander Carballo
8. Luan F. R. Jesus

In Computer Vision and Pattern Recognition

1. Ekim Yurtsever
2. Alexander Carballo
3. Jacob Lambert
4. Vinicius B. Cardoso
5. Thiago Oliveira-Santos
6. Raphael V. Carneiro
7. Pedro Azevedo
8. A. D. Souza

Citations in the corpus

• A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2019, background): “algorithms [184] are often employed, which ensures tracking algorithms can recover from poor data association at any single time step.”
• Self-Driving Cars: A Survey (2019, methodology): “whether a cluster is a vehicle or not. Data association is solved by an optimization algorithm. A Multiple Hypothesis Tracking (MHT) algorithm is employed to mitigate association errors. Hwang et al. [HWA16] use images captured by a monocular camera to filter out 3D LIDAR points that do not belong t”