University of Twente Student Theses
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Performance and Feasibility of Real-Time Gesture Recognition on Consumer-Grade Computers
Solodkyi, Illia (2025) Performance and Feasibility of Real-Time Gesture Recognition on Consumer-Grade Computers.
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| Abstract: | The availability of gesture recognition technologies raises the potential for improvement of human-computer interaction and the adoption of gesture recognition as a widely used way of interaction. Adoption continues to be limited on consumer-grade computers because of concerns about high processing demands and specialized hardware requirements. This study assesses the feasibility of implementing webcam-based gesture-controlled interfaces on typical consumer-grade computers without decreasing overall system performance. Multiple machine learning models, including traditional classifiers and boosted trees, were trained and benchmarked for real-time CPU, GPU, and RAM usage. Optimization techniques such as pre-pruning and frame skipping were applied to reduce resource demands. Resource consumption was estimated for several types of real-world computer configurations, from highend desktops to low-cost laptops. The results show that models with the adoption of optimization techniques can achieve high accuracy while consuming less than 2% of computational power, making real-time gesture recognition feasible for the majority of consumer-grade computers, with the exception of low-end laptops with constrained processing power. This research highlights key system requirements, trade-offs, and future directions to encourage broader adoption of gesture-based interfaces on consumer-grade computers. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Business & IT BSc (56066) |
| Link to this item: | https://purl.utwente.nl/essays/107372 |
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