Semantic Scholar Open Access 2019 89 sitasi

Celebrities-ReID: A Benchmark for Clothes Variation in Long-Term Person Re-Identification

Y. Huang Qiang Wu Jingsong Xu Yi Zhong

Lihat Sumber DOI

Abstrak

This paper considers person re-identification (re-ID) in the case of long-time gap (i.e., long-term re-ID) that concentrates on the challenge of clothes variation of each person. We introduce a new dataset, named Celebrities-reID to handle that challenge. Compared with current datasets, the proposed Celebrities-reID dataset is featured in two aspects. First, it contains 590 persons with 10,842 images, and each person does not wear the same clothing twice, making it the largest clothes variation person re-ID dataset to date. Second, a comprehensive evaluation using state of the arts is carried out to verify the feasibility and new challenge exposed by this dataset. In addition, we propose a benchmark approach to the dataset where a two-step fine-tuning strategy on human body parts is introduced to tackle the challenge of clothes variation. In experiments, we evaluate the feasibility and quality of the proposed Celebrities-reID dataset. The experimental results demonstrate that the proposed benchmark approach is not only able to best tackle clothes variation shown in our dataset but also achieves competitive performance on a widely used person re-ID dataset Market1501, which further proves the reliability of the proposed benchmark approach.

Topik & Kata Kunci

Computer Science

Penulis (4)

Y. Huang

Qiang Wu

Jingsong Xu

Yi Zhong

Format Sitasi

APA MLA BibTeX

Huang, Y., Wu, Q., Xu, J., Zhong, Y. (2019). Celebrities-ReID: A Benchmark for Clothes Variation in Long-Term Person Re-Identification. https://doi.org/10.1109/IJCNN.2019.8851957

Akses Cepat

Lihat di Sumber doi.org/10.1109/IJCNN.2019.8851957

Informasi Jurnal

Tahun Terbit: 2019
Bahasa: en
Total Sitasi: 89×
Sumber Database: Semantic Scholar
DOI: 10.1109/IJCNN.2019.8851957
Akses: Open Access ✓