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Orientador(es)
Resumo(s)
This paper consists of a bibliometric study that covers the topic of 3D object detection from
2022 until the present day. It employs various analysis approaches that shed light on the leading
authors, affiliations, and countries within this research domain alongside the main themes of interest
related to it. The findings revealed that China is the leading country in this domain given the fact
that it is responsible for most of the scientific literature as well as being a host for the most productive
universities and authors in terms of the number of publications. China is also responsible for initiating
a significant number of collaborations with various nations around the world. The most basic theme
related to this field is deep learning, along with autonomous driving, point cloud, robotics, and
LiDAR. The work also includes an in-depth review that underlines some of the latest frameworks
that took on various challenges regarding this topic, the improvement of object detection from point
clouds, and training end-to-end fusion methods using both camera and LiDAR sensors, to name
a few.
Descrição
Palavras-chave
3D object Object detection Object orientation Bibliometric analysis
Contexto Educativo
Citação
Yahia, Youssef; Lopes, Júlio Castro; Lopes, Rui Pedro (2023). Computer vision algorithms for 3D object recognition and orientation: a bibliometric study. Electronics. eISSN 2079-9292. 12:20, p. 1-16
Editora
MDPI