Driver-Gaze Zone Estimation Using Bayesian Filtering and Gaussian Processes
| Autor: | Tomas McKelvey, Lars Hammarstrand, Malin Lundgren |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Estimation
050210 logistics & transportation Computer science business.industry Mechanical Engineering 05 social sciences Probabilistic logic 02 engineering and technology Function (mathematics) Gaze Computer Science Applications symbols.namesake 0502 economics and business Automotive Engineering 0202 electrical engineering electronic engineering information engineering symbols 020201 artificial intelligence & image processing Computer vision Artificial intelligence Focus (optics) Set (psychology) business Gaussian process Complement (set theory) |
| Zdroj: | IEEE Transactions on Intelligent Transportation Systems. 17:2739-2750 |
| ISSN: | 1558-0016 1524-9050 |
| DOI: | 10.1109/tits.2016.2526050 |
| Popis: | In this paper, we propose a Bayesian filtering approach that uses information from camera-based driver monitoring systems and filtering techniques to find the probability that the driver is looking in different zones. In particular, the focus is on a set of zones directly related either to active driving or to visual distraction, such as the road, the mirrors, the infotainment display, or control buttons. For systems that do not provide direct observations of the gaze direction or as a complement to noisy gaze data, we propose to use probabilistic functions that describe the gaze direction as a function of head pose and eye closure. It is further shown how these functions can be estimated from data with know visual focus points using Gaussian processes. Evaluation on data from two driver monitoring systems shows a significant improvement compared with the gaze zone estimates based on unprocessed data. |
| Databáze: | OpenAIRE |
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