2024-10-26 –, CLASS #4
Language: English
Facial recognition in low light conditions is a big challenge for traditional facial recognition systems. In this talk, the speaker will delve into how each of various dark image feature extraction algorithms (HOG, LBP, Fisherface, DeepID, etc), implemented using Python, can significantly impact facial recognition performance in low lighting condition based on speaker's research.
This talk will be useful for students, researchers, developers, and practitioners who are interested in facial recognition and computer vision.
Facial recognition in low light conditions is a big challenge for traditional facial recognition systems. In this talk, the speaker will delve into how each of various dark image feature extraction algorithms (HOG, LBP, Fisherface, DeepID, etc), implemented using Python, can significantly impact facial recognition performance in low lighting condition based on speaker's research.
Some important points that will be discussed:
- The challenges of facial recognition in low light conditions and how current solutions.
- Detail explanation about how several feature extraction algorithms work.
- Differences in several feature extraction algorithms.
- Selecting the most effective feature extraction algorithm for low-light facial recognition.
Hello...
I am Silvia, a dedicated computer vision and software engineer with almost 2 years of experience and has completed several computer vision projects. Currently, I am working as a Software Engineer in GAOGAO Pte. Ltd.
I was graduated as a bachelor of engineering majoring Information Technology and I delve into the field of artificial intelligence, especially computer vision, since 2022. I did research in this area during my time at university and will publish 2 papers this year.
I also really enjoy discussing AI and the latest technology. Feel free to reach out to me on LinkedIn if you'd like to discuss about it.