Title :
Visual detection of vehicles using a bag-of-features approach
Author :
Pinto, Patricio ; Tome, Ana ; Santos, Vitor
Author_Institution :
DEM Univ. of Aveiro, Aveiro, Portugal
Abstract :
This paper presents and evaluates the performance of a method for vehicle detection using a bag-of-features methodology. The algorithm combines Speeded Up Robust Features with a Support Vector Machine. An optimization to the bag-of-features dictionary based on a genetic algorithm for attribute selection is also described. The results obtained show that this method can successfully address the problem of vehicle classification.
Keywords :
image classification; object detection; optimisation; road vehicles; support vector machines; attribute selection; bag-of-features approach; genetic algorithm-based bag-of-features dictionary; speeded up robust features; support vector machine; vehicle classification; vehicle visual detection; Dictionaries; Feature extraction; Kernel; Optimization; Support vector machines; Vehicles; Visualization; Genetic algorithms; Intelligent vehicles; Machine learning algorithms; Object recognition; Support vector machines;
Conference_Titel :
Autonomous Robot Systems (Robotica), 2013 13th International Conference on
Conference_Location :
Lisbon
Print_ISBN :
978-1-4799-1246-9
DOI :
10.1109/Robotica.2013.6623539
