Comparison of different approaches to visual terrain classification for outdoor mobile robots ?
Ten color or texture descriptors and three classifiers have been evaluated for visual terrain classification. JCD can represent different terrain images with significant interclass discrepancies. ELM has mild optimization constraints and obtains better generalization performance. We experimentally evaluate the descriptors and classifiers over two real world datasets. The combination of JCD descriptor and ELM classifier shows higher rate of effectiveness than traditional methods.
terrain classification image classification image descriptor compact composite descriptor extreme learning machine