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Full-Text Articles in Engineering
A Precise Attention Tracking System Based On Computer Vision, Jiyuan Liu, Hanwen Qi, Zhicheng Liu, Minrui Fei, Kun Zhang
A Precise Attention Tracking System Based On Computer Vision, Jiyuan Liu, Hanwen Qi, Zhicheng Liu, Minrui Fei, Kun Zhang
Journal of System Simulation
Abstract: A precise attention tracking system based on machine vision is designed to address the difficulty in studying students' attention allocation. The system includes an image capture device and an accurate attention tracking algorithm. The image capture device can capture the clearer ocular images. The pupil center localization algorithm replaces VGG16 with lightweight MobileNetv3 and uses twostage feature fusion and center keypoint prediction techniques to improve the speed and accuracy. The algorithm achieves a speed of up to 36 frames/s and 97.42% accuracy. The gaze tracking algorithm compensates for the head movements to achieve the meticulous gaze tracking. An interactive …
Conditional Dilated Attention Tracking Model - C-Datm, Tyler Clayton Highlander
Conditional Dilated Attention Tracking Model - C-Datm, Tyler Clayton Highlander
Browse all Theses and Dissertations
Current commercial tracking systems do not process images fast enough to perform target-tracking in real- time. State-of-the-art methods use entire scenes to locate objects frame-by-frame and are commonly computationally expensive because they use image convolutions. Alternatively, attention mechanisms track more efficiently by mimicking human optical cognitive interaction to only process small portions of an image. Thus, in this work we use an attention-based approach to create a model called C-DATM (Conditional Dilated Attention tracking Model) that learns to compare target features in a sequence of image-frames using dilated convolutions. The C-DATM is tested using the Modified National Institute of Standards …