Vehicle Attribute Recognition by Appearance: Computer Vision Methods for Vehicle Type, Make and Model Classification
Ni, Xingyang; Huttunen, Heikki (2020)
Ni, Xingyang
Huttunen, Heikki
2020
Journal of Signal Processing Systems
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202007076341
https://urn.fi/URN:NBN:fi:tuni-202007076341
Kuvaus
Peer reviewed
Tiivistelmä
This paper studies vehicle attribute recognition by appearance. In the literature, image-based target recognition has been extensively investigated in many use cases, such as facial recognition, but less so in the field of vehicle attribute recognition. We survey a number of algorithms that identify vehicle properties ranging from coarse-grained level (vehicle type) to fine-grained level (vehicle make and model). Moreover, we discuss two alternative approaches for these tasks, including straightforward classification and a more flexible metric learning method. Furthermore, we design a simulated real-world scenario for vehicle attribute recognition and present an experimental comparison of the two approaches.
Kokoelmat
- TUNICRIS-julkaisut [19304]