Title
Semi-autonomous reference data generation for perception performance evaluation
Abstract
In the development phase of perception systems (e.g. for advanced driver assistance systems) general interest is pointing towards the performance of the respective detection and tracking algorithms. One common way to evaluate such systems relies on simulated data which is used as a reference. We present a semi-autonomous method, which allows the extraction of reference data from sensor recordings (including data at least from a camera and a distance measuring sensor device). Furthermore, we show how to combine these reference data with the output from the object detection system and how to derive performance statistics (detection and miss rates) of the system. As the generated reference information can be stored along with the sensor recordings, this method also facilitates the comparison of different software versions or algorithm parameters.
Year
DOI
Venue
2007
10.1109/ICIF.2007.4408000
Fusion
Keywords
Field
DocType
algorithm parameters,semi-autonomous method,sensor recording,object detection system,reference data generation,performance evaluation,perception systems,software versions,statistics,reference data,data mining,databases
Reference data (financial markets),Computer vision,Object detection,Computer science,Advanced driver assistance systems,Artificial intelligence,Perception,Software versioning
Conference
ISBN
Citations 
PageRank 
978-0-662-45804-3
4
0.49
References 
Authors
1
5
Name
Order
Citations
PageRank
Thomas Tatschke181.57
Franz-Josef Färber240.49
Erich Fuchs3423.45
Leonhard F. Walchshäusl471.28
Rudi Lindl560.94