Tommi Tykkala

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In RGB-D sensor based visual odometry the goal is to estimate a sequence of camera movements using image and/or range measurements. Direct methods solve the problem by minimizing intensity error. In this work a depth map obtained from a RGB-D sensor is considered as a new measurement which is combined with a direct photometric cost function. The(More)
In this work, a real-time image-based camera tracker is designed for live television production studios. The major concern is to decrease camera tracking expenses by an affordable vision-based approach. First, a dense keyframe model of the static studio scene is generated using image-based dense tracking and bundle adjustment. Online camera tracking is then(More)
In this paper a dense structure model is developed for stereo image based Simultaneous Localization And Mapping (SLAM). It is proposed to model dense environment structure incrementally by robustly integrating disparity maps from current and previous time instants. In this way disparities can be refined over time to favor consistent 3D structure over noise.(More)
In this work, a RGB-D input stream is utilized for GPU-boosted 3D reconstruction of textured indoor environments. The goal is to develop a process which produces standard 3D models from indoors to explore them virtually. Camera motion is tracked in 3D space by registering the current view with a reference view. Depending on the trajectory shape, the(More)
In this work, a real-time image-based camera tracking solution is developed for television broadcasting studio environments. An affordable vision-based system is proposed which can compete with expensive matchmoving systems. The system requires merely commodity hardware: a low cost RGB-D sensor and a standard laptop. The main contribution is avoiding(More)
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