Muhammad S. Alam1,5,*, Farhan B. Mohamed1,3, Ali Selamat2, Faruk Ahmed4, AKM B. Hossain6,7
Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 417-436, 2024, DOI:10.32604/iasc.2024.051999
Abstract Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems. The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed. This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence. An annotated image dataset trains the proposed system and predicts the camera pose in real-time. The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera More >
Login
Register
