In this paper we tackle the problem of vehicle re-identification in a camera network utilizing triplet embeddings. Re-identification is the problem of matching appearances of
objects across different cameras. With the proliferation of surveillance cameras enabling
smart and safer cities, there is an ever-increasing need to re-identify vehicles across cameras. Typical challenges arising in smart city scenarios include variations of viewpoints,
illumination and self occlusions. Most successful approaches for re-identification involve
(deep) learning an embedding space such that the vehicles of same identities are projected
closer to one another, compared to the vehicles representing different identities. Popular
loss functions for learning an embedding (space) include contrastive or triplet loss. In this
paper we provide an extensive evaluation of triplet loss applied to vehicle re-identification
and demonstrate that using the recently proposed sampling approaches for mining informative data points outperform most of the existing state-of-the-art approaches for vehicle
re-identification. Compared to most existing state-of-the-art approaches, our approach
is simpler and more straightforward for training utilizing only identity-level annotations,
along with one of the smallest published embedding dimensions for efficient inference.
Furthermore in this work we introduce a formal evaluation of a triplet sampling variant
(batch sample) into the re-identification literature. In addition to the conference version
[24], this submission adds extensive experiments on new released datasets, cross domain
evaluations and ablation studies.
Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies
Informacja
SZANOWNI CZYTELNICY!
UPRZEJMIE INFORMUJEMY, ŻE BIBLIOTEKA FUNKCJONUJE W NASTĘPUJĄCYCH GODZINACH:
Wypożyczalnia i Czytelnia Główna: poniedziałek – piątek od 9.00 do 19.00