VIDEO TRACKING USING PARTICLE FILTER AND ORB FOR VISUAL SERVOING APPLICATION - HENDRO NUGROHO (NIM : 23215084), TSANI
Visual servoing has been widely used in various sectors such as manufacturing, transportation, health, and security. In the security sector such as the use of video surveillance, visual servoing requires the ability to be able to track various objects in complex environments and in various lighting conditions. The classical approach in feature extraction, such as using fiducial marker, is not possible in this condition. Instead, the integration of video tracking algorithms can be done to handle the feature extraction process. Video tracking is the process to predict the position of an objectÃ‚Â’s feature(s) in a sequence of images recorded by the camera continuously. In order to be used in real-time systems such as visual servoing, video tracking must be efficient, high precision, and robust. For this purpose, we propose a modification of color-based particle filter algorithm using results from the ORB feature detector. With this modification, the particle filter algorithm for video tracking has low computing power because the number of particles used can be significantly reduced while maintaining its accuracy. Comparison of tracking performance with particle filter algorithm without modification is done and we get the result as expected. Performance test of tracking algorithm is also performed for various conditions such as rotation, scale, change of illumination, occlusion, and also clutter with the result of increasing the accuracy and stability. Integration with the visual servoing system also shows good performance and can be used for tracking various objects in indoor and outdoor environments.