Evolution of Visual Odometry Techniques
원문 초록
With rapid advancements in the area of mobile robotics and industrial automation, a growing need has arisen towards accurate navigation and localization of moving objects. Camera based motion estimation is one such technique which is gaining huge popularity owing to its simplicity and use of limited resources in generating motion path. In this paper, an attempt is made to introduce this topic for beginners covering different aspects of vision based motion estimation task. The evolution of VO schemes over last few decades is discussed under two broad categories, that is, geometric and non-geometric approaches. The geometric approaches are further detailed under three different classes, that is, feature-based, appearance-based, and a hybrid of feature and appearance based schemes. The non-geometric approach is one of the recent paradigm shift from conventional pose estimation technique and is thus discussed in a separate section. Towards the end, a list of different datasets for visual odometry and allied research areas are provided for a ready reference.
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DINO-VO: A Feature-based Visual Odometry Leveraging a Visual Foundation Model
UMotion: Uncertainty-driven Human Motion Estimation from Inertial and Ultra-wideband Units
An Online Adaptation Method for Robust Depth Estimation and Visual Odometry in the Open World
ForestVO: Enhancing Visual Odometry in Forest Environments through ForestGlue
cuVSLAM: CUDA accelerated visual odometry and mapping
Self-Supervised Monocular Visual Drone Model Identification through Improved Occlusion Handling
토론
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