Fabio F. de Oliveira
Papers
1
Total Citations
12
H-Index
1
About
Fabio F. de Oliveira is a researcher whose work lies at the intersection of computer vision, 3D object recognition, and sensor technology. His most influential contribution, "Efficient 3D Objects Recognition Using Multifoveated Point Clouds" (2018, 12 citations), addresses a critical bottleneck in real-time 3D perception: the computational burden of processing dense point clouds from modern RGB-D sensors. By introducing a multifoveated approach—inspired by biological vision—de Oliveira’s method selectively allocates processing resources to salient regions, dramatically improving recognition efficiency without sacrificing accuracy. This innovation is particularly significant for robotics and autonomous systems, where rapid, reliable object identification is essential. Beyond this flagship work, de Oliveira’s research continues to explore how hardware and algorithmic co-design can unlock the full potential of 3D sensing. His contributions are helping to bridge the gap between raw sensor data and practical, real-world applications, making him a notable figure in the ongoing evolution of 3D computer vision.
Research Focus
Key Achievements
Top Papers
- 1Efficient 3D Objects Recognition Using Multifoveated Point Clouds12 citations · 2018