Now showing items 11-13 of 13
Real-Time Eyeblink Detector and Eye State Classifier for Virtual Reality (VR) Headsets (Head-Mounted Displays, HMDs)
The aim of the study is to develop a real-time eyeblink detection algorithm that can detect eyeblinks during the closing phase for a virtual reality headset (VR headset) and accordingly classify the eye’s current state (open or closed). The proposed method utilises analysis of a motion vector for detecting eyelid closure, and a Haar cascade classifier (HCC) for localising the eye in the captured frame. When the downward motion vector (DMV) is detected, a cross-correlation between the current region of interest (eye ...
Topic space trajectories
The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers it becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present topic space trajectories, a structure that allows for the comprehensible tracking ...
Toward optimal probabilistic active learning using a Bayesian approach
Gathering labeled data to train well-performing machine learning models is one of the critical challenges in many applications. Active learning aims at reducing the labeling costs by an efficient and effective allocation of costly labeling resources. In this article, we propose a decision-theoretic selection strategy that (1) directly optimizes the gain in misclassification error, and (2) uses a Bayesian approach by introducing a conjugate prior distribution to determine the class posterior to deal with uncertainties. ...