Publications

@article{biswas_video_2021,

title = {A video summarization approach to speed-up the analysis of child sexual exploitation material},

author = {Rubel Biswas and Deisy Chaves and Laura Fernández-Robles and Eduardo Fidalgo and Enrique Alegre},

url = {https://ruc.udc.es/dspace/handle/2183/28353},

year  = {2021},

date = {2021-01-01},

journal = {XLII Jornadas de Automática},

pages = {648–654},

abstract = {This paper presents a video summarization strategy combining perceptual hashing and face detection to identify key frames from videos, specifically targeting content with faces that may relate to victims or offenders. The proposed approach is tested on adult pornography detection using the NDPI-800 dataset, achieving 84.15% accuracy and a speed of 8.05 ms/frame, making it suitable for real-time applications. This method can also create video summaries while preserving distinctive faces from the original footage.},

note = {Publisher: Universidade da Coruña, Servizo de Publicacións},

keywords = {content detection, face detection, perceptual hashing, real time applications, video summarization},

pubstate = {published},

tppubtype = {article}

}

@article{chaves_improving_2019,

title = {Improving Speed-Accuracy Trade-off in Face Detectors for Forensic Tools by Image Resizing},

author = {Deisy Chaves and Eduardo Fidalgo and Enrique Alegre and Pablo Blanco-Medina},

url = {https://www.researchgate.net/profile/Deisy-Chaves/publication/345312886_Improving_Speed-Accuracy_Trade-off_in_FaceDetectors_for_Forensic_Tools_by_Image_Resizing/links/5fa39e3b92851cc28695f323/Improving-Speed-Accuracy-Trade-off-in-FaceDetectors-for-Forensic-Tools-by-Image-Resizing.pdf},

year  = {2019},

date = {2019-01-01},

journal = {V Jornadas Nacionales De Investigación en Ciberseguridad},

volume = {1},

number = {1},

pages = {222–223},

abstract = {This study proposes a strategy to improve face detection speed and accuracy in forensic material analysis, especially for Child Sexual Abuse cases. The method focuses on image resizing to enhance the performance of three deep-learning-based face detectors while ensuring real-time application capability. The results show that resizing images to 50% of their original size strikes the best balance between speed and accuracy, allowing faster face detection with minimal loss in performance.},

note = {Publisher: Universidad de Cáceres},

keywords = {CSA, deep learning, face detection, Forensic Images},

pubstate = {published},

tppubtype = {article}

}