IECE Transactions on Emerging Topics in Artificial Intelligence | Volume 2, Issue 2: 57-67, 2025 | DOI: 10.62762/TETAI.2025.279350
Abstract
Predicting personality traits automatically has emerged as a challenging problem in computer vision. This paper introduces an innovative multimodal feature learning framework for personality analysis in short video clips. For visual processing, we construct a facial graph and design a Geo-based two-stream network incorporating an attention mechanism, leveraging both Graph Convolutional Networks (GCN) and Convolutional Neural Networks (CNN) to capture static facial expressions. Additionally, ResNet18 and VGGFace networks are employed to extract global scene and facial appearance features at the frame level. To capture dynamic temporal information, we integrate a BiGRU with a temporal attentio... More >
Graphical Abstract
