View Item 
        •   Utrecht University Student Theses Repository Home
        • UU Theses Repository
        • Theses
        • View Item
        •   Utrecht University Student Theses Repository Home
        • UU Theses Repository
        • Theses
        • View Item
        JavaScript is disabled for your browser. Some features of this site may not work without it.

        Browse

        All of UU Student Theses RepositoryBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

        Neural multi-view segmentation-aggregation for joint Lidar and image object detection

        Thumbnail
        View/Open
        thesis_bvansomeren_3769240.pdf (21.49Mb)
        Publication date
        2017
        Author
        Someren, B. van
        Metadata
        Show full item record
        Summary
        Combining different types of data from multiple views makes it easier to perform object detection. Our novel method enables multi-view deep convolutional neural networks to combine color information from panoramic images and depth information derived from Lidar point clouds for improved street furniture detection. Our focus is on the prediction of world positions of light poles specifically. In contrast to related methods, our method operates on data from real world environments consisting of many complex objects and supports the combination of information from recording locations that do not have fixed relative positions.
        URI
        https://studenttheses.uu.nl/handle/20.500.12932/27083
        Collections
        • Theses
        Utrecht university logo