Visual Place Recognition
This work addresses location identification for autonomous driving safety, but it appears incremental as it compares existing HMM variants without introducing a new method.
The paper tackled visual place recognition for autonomous driving by comparing HMM filter and HMM smoother algorithms, finding that the HMM smoother outperformed the filter in prediction accuracy.
Visual position recognition affects the safety and accuracy of automatic driving. To accurately identify the location, this paper studies a visual place recognition algorithm based on HMM filter and HMM smoother. Firstly, we constructed the traffic situations in Canberra city. Then the mathematical models of the HMM filter and HMM smoother were performed. Finally, the vehicle position was predicted based on the algorithms. Experiment results show that HMM smoother is better than HMM filter in terms of prediction accuracy.