Evaluation of Embedded Systems for Automotive Image Processing
| Autor: | Byun Jin Young, Jae Wook Jeon, Trung Tin Duong, Jung Hwan Seo, Thi Dinh Tran |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
050210 logistics & transportation
Computer science business.industry Computation 05 social sciences Automotive industry Image processing 02 engineering and technology Power (physics) Set (abstract data type) Transfer (computing) Embedded system 0502 economics and business Personal computer 0202 electrical engineering electronic engineering information engineering Benchmark (computing) 020201 artificial intelligence & image processing business |
| Zdroj: | SNPD |
| Popis: | With the emergence of industry 4.0, autonomous driving vehicles have become an exciting research topic in the science technology community. The driving system requires many complex algorithms that provide both accurate results and fast running times. However, the performance of these algorithms is usually limited to standard personal computer (PC) systems. Currently, the computation power of available embedded systems lags far behind that of a standard PC, even when compared to PCs with moderate capabilities. Hence, we present some benchmark results of several systems, including standard PCs, laptops, and embedded systems, for performing computer vision algorithms. We collected a set of algorithms that are commonly used in autonomous driving systems and then ran each of these on our selected systems. In this evaluation, we focused only on the processing time without concerning about the precision of the algorithm. The details of the testing algorithms and systems are provided in this report also. We believe that our experiment can provide practical information to people who aim to transfer their algorithm to an embedded system. |
| Databáze: | OpenAIRE |
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