Katharina Seifert

Evaluation of Six Night Vision Enhancement Systems: Qualitative and Quantitative Support for Intelligent Image Processing

Objective: An evaluation study was conducted to answer the question of which system properties of night vision enhancement systems (NVESs) provide a benefit for drivers without increasing their workload. Background: Different infrared sensor, image processing, and display technologies can be integrated into an NVES to support nighttime driving. Because each of these components has its specific strengths and weaknesses, careful testing is required to determine their best combination. Method: Six prototypical systems were assessed in two steps. First, a heuristic evaluation with experts from ergonomics, perception, and traffic psychology was conducted. It produced a broad overview of possible effects of system properties on driving. Based on these results, an experimental field study with 15 experienced drivers was performed. Criteria used to evaluate the development potential of the six prototypes were the usability dimensions of effectiveness, efficiency, and user satisfaction (International Organization for Standardization, 1998). Results: Results showed that the intelligibility of information, the easiness with which obstacles could be located in the environment, and the position of the display presenting the output of the system were of crucial importance for the usability of the NVES and its acceptance. Conclusion: All relevant requirements are met best by NVESs that are positioned at an unobtrusive location and are equipped with functions for the automatic identification of objects and for event-based warnings. Application: These design recommendations and the presented approach to evaluate the systems can be directly incorporated into the development process of future NVESs.

Car-seat occupancy detection using a monocular 360° NIR camera and advanced template matching

The integration of seat occupancy detection systems is one of the most recent developments in automobile production. These systems prevent the deployment of airbags at unoccupied seats, thus avoiding the considerable cost imposed by the replacement of airbags. Seat-occupancy detection system can also be used to improve passenger comfort, e.g. by an occupation-dependent control of air-conditioning systems. This paper describes an inexpensive and versatile optical seat-occupancy detection system. Different approaches to pattern matching and the impact of local normalization, edge detection, multi-algorithm and temporal matching-score fusion are evaluated for each individual seat using a test set of 53,928 frames further classified in uniform and non-uniform illumination conditions. The results of these tests yield Equal Error Rates for uniform/non-uniform illumination of as low as 3.05%/1.68% for the front left seat, 2.17%/0.69% for the front right seat, 5.86%/4.01% for the rear left seat, 10.99%/11.07% for the rear center seat and 5.63%/1.84% for the rear right seat. The test results indicate that at least the two seat rows should be treated differently in terms of the selection of classification algorithms.