CPA-SLAM: consistent plane-model alignment for direct RGB-d slam - 2016 PROJECT TITLE : CPA-SLAM: consistent plane-model alignment for direct RGB-d slam - 2016 ABSTRACT: Planes are predominant options of artificial environments which have been exploited in several mapping approaches. During this paper, we tend to propose a real-time capable RGB-D SLAM system that consistently integrates frame-to-keyframe and frame-to-plane alignment. Our method models the environment with a global plane model and - besides direct image alignment - it uses the planes for tracking and world graph optimization. This way, our technique makes use of the dense image data on the market in keyframes for correct short-term tracking. At the identical time it uses a global model to scale back drift. Each elements are integrated consistently in an expectation-maximization framework. In experiments, we demonstrate the advantages our approach and its state-of-the-art accuracy on difficult benchmarks. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Image Segmentation Image Colour Analysis Object Tracking Slam (Robots) Expectation-Maximisation Algorithm Enhanced Ultrasound Image Reconstruction Using A Compressive Blind Deconvolution Approach - 2017 A local structure and direction-aware optimization approach for three-dimensional tree modeling - 2016