Maximizing Efficiency in Real‑time Invariant Object Detection: A Multi‑Algorithm Approach
HCII ’24 • URCA ’24 • Research · Cursor detection & tracking
Abstract
We propose and evaluate three algorithmic iterations for detecting and tracking invariant objects (e.g., computer cursors) across video frames. Each edition targets distinct computational budgets and research constraints.
Approach
- Classical image processing baseline for rapid detection.
- Feature‑based tracking for robustness under occlusion and motion blur.
- Hybrid pipeline balancing accuracy and real‑time performance.
Results
- Consistent frame‑rate on consumer hardware with tunable quality levels.
- Improved precision/recall versus single‑method baselines.
Publication
Presented at HCII 2024 and URCA 2024. Contact for manuscript.