{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/emotion-estimation-from-video-footage-with","title":"Emotion estimation from video footage with LSTM","arxiv_id":"2501.13432","date":"2025-01-23","proceeding":null,"authors":["Samer Attrah"],"abstract":"Emotion estimation in general is a field that has been studied for a long time, and several approaches exist using machine learning. in this paper, we present an LSTM model, that processes the blend-shapes produced by the library MediaPipe, for a face detected in a live stream of a camera, to estimate the main emotion from the facial expressions, this model is trained on the FER2013 dataset and delivers a result of 71% accuracy and 62% f1-score which meets the accuracy benchmark of the FER2013 dataset, with significantly reduced computation costs. https://github.com/Samir-atra/Emotion_estimation_from_video_footage_with_LSTM_ML_algorithm","url_abs":"https://arxiv.org/abs/2501.13432v3","url_pdf":"https://arxiv.org/pdf/2501.13432v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"emotion-estimation-from-video-footage-with","repo_url":"https://github.com/samir-atra/emotion_estimation_from_video_footage_with_lstm_ml_algorithm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"3d-facial-expression-recognition","task_name":"3D Facial Expression Recognition"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":null,"method_name":"Library"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[{"slug":"fer2013-blendshapes","name":"FER2013 Blendshapes","full_name":"FER2013 blendshapes dataset example (Partial)"}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}