Back to Search
Start Over
Vehicle recognition model for complex scenarios based on human memory mechanism.
- Source :
-
Journal of Intelligent & Fuzzy Systems . 2020, Vol. 38 Issue 6, p7825-7835. 11p. - Publication Year :
- 2020
-
Abstract
- The prevailing vehicle recognition technology is adversely affected by the environment such as complex traffic scenarios and weather conditions. This paper proposes a robust vehicle recognition model based on human memory mechanism named Memory-based Vehicle Recognition Model (MVRM). Motivated by the success of memory and attention mechanism, we explore some features of human visual attention model. Fusing short term and long-term memory modules together yield deeper architectures recognizing increasing complex environmental scenarios. Firstly, a rare motion feature has been introduced to measure the visual salience, which improves the accuracy of the visual attention mechanism. Second, a model of vehicle salient region recognition has been established. The results of experiments show that the dynamic vehicle recognition rate of MVRM is 77.10%, while its false recognition rate has only a nominal value of ∼4.5%. Furthermore, the model offers good recognition of vehicle targets under complex environment conditions related to weather and road traffic. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MEMORY
*VEHICLE models
*SHORT-term memory
*EDUCATIONAL tests & measurements
Subjects
Details
- Language :
- English
- ISSN :
- 10641246
- Volume :
- 38
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Publication Type :
- Academic Journal
- Accession number :
- 144257177
- Full Text :
- https://doi.org/10.3233/JIFS-179852