Privacy protection is a very important issue, in the context of social media and GDPR. This lecture overviews the face de-identification problem from an engineering perceptive. In principle, face de-identification methods aim on calculating an affine or a non-linear transformation to an input facial image, so that the depicted person identity is no longer recognized… Continue reading Face De-identification for Privacy and Protection
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Face Clustering
This lecture overviews Face Clustering that has many applications in Human-centered Computing, Image and Video Analysis and Social Media Analytics. It covers the following topics in detail: Facial image similarities. Similarity graphs. N-cut clustering. Applications.
Face Recognition
This lecture overviews that has many applications in Human-centered Computing, Image and Video Analysis, Surveillance and Social Media Analytics. It covers the following topics in detail: Face recognition/identification. Face verification. Performance evaluation. Traditional face recognition methods (subspace, EGM). DNN face recognition. Facial label propagation.
Crowd Detection and Analysis
This lecture overviews Crowd Detection and Analysis that has many applications in Human-centered Computing, Image and Video Analysis and Smart City applications and surveillance. It covers the following topics in detail: Pedestrian Detection. Crowd Detection. Crowd Counting/Density. Crowd Tracking. Crowd Behavior Analysis.
Face and Object De-detection
This lecture overviews Face and Object De-detection that has many applications in Human-centered Computing and privacy protection in Social or Broadcasted Media. It covers the following topics in detail: Object detection and de-detection definitions. Adversarial Attacks: Threat Model, Perturbation, Attack Methods, Attack Scenarios, Defense Methods, Benchmarking. Face Detection Obfuscation.
Face Detection
This lecture overviews Face Detection that has many applications in Human-centered Computing, Image and Video Analysis and Social Media Analytics. It covers the following topics in detail: Face Detection definition: Regression and Classification. Face detection metrics. DNN face detection.