Understanding videos with face recognition: a complete pipeline and applications

Pasquale Lisena*, Jorma Laaksonen, Raphaël Troncy

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

Abstrakti

When browsing or studying a video corpus, particularly relevant information consists in knowing who are the people appearing in the scenes. In this paper, we show how a combination of state of the art techniques can be organised in a pipeline for face recognition of celebrities. In particular, we propose a system which combines MTCNN for detecting faces and FaceNet for extracting face embeddings, which are used to train a set of classifiers. The face recognition results obtained at a frame level are then combined with those in consecutive frames, relying on automatic object tracking. Differently from previous work, we use images automatically retrieved by web search engines. We evaluate the systems one three datasets including historical videos from 1945 to 1969 and contemporary videos, obtaining a good precision score. In addition, we show how the obtained results can be applied to foster historical studies.

AlkuperäiskieliEnglanti
Sivut2147-2159
Sivumäärä13
JulkaisuMULTIMEDIA SYSTEMS
Vuosikerta28
Numero6
Varhainen verkossa julkaisun päivämäärä15 kesäk. 2022
DOI - pysyväislinkit
TilaJulkaistu - jouluk. 2022
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

Sormenjälki

Sukella tutkimusaiheisiin 'Understanding videos with face recognition: a complete pipeline and applications'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

Siteeraa tätä