3D Object Detection and Localization Using Multimodal Point Pair Features. Drost, B. & Ilic, S. In Visualization Transmission 2012 Second International Conference on 3D Imaging, Modeling, Processing, pages 9–16, October, 2012. doi abstract bibtex Object detection and localization is a crucial step for inspection and manipulation tasks in robotic and industrial applications. We present an object detection and localization scheme for 3D objects that combines intensity and depth data. A novel multimodal, scale- and rotation-invariant feature is used to simultaneously describe the object's silhouette and surface appearance. The object's position is determined by matching scene and model features via a Hough-like local voting scheme. The proposed method is quantitatively and qualitatively evaluated on a large number of real sequences, proving that it is generic and highly robust to occlusions and clutter. Comparisons with state of the art methods demonstrate comparable results and higher robustness with respect to occlusions.
@inproceedings{drost_3d_2012,
title = {{3D} {Object} {Detection} and {Localization} {Using} {Multimodal} {Point} {Pair} {Features}},
doi = {10.1109/3DIMPVT.2012.53},
abstract = {Object detection and localization is a crucial step for inspection and manipulation tasks in robotic and industrial applications. We present an object detection and localization scheme for 3D objects that combines intensity and depth data. A novel multimodal, scale- and rotation-invariant feature is used to simultaneously describe the object's silhouette and surface appearance. The object's position is determined by matching scene and model features via a Hough-like local voting scheme. The proposed method is quantitatively and qualitatively evaluated on a large number of real sequences, proving that it is generic and highly robust to occlusions and clutter. Comparisons with state of the art methods demonstrate comparable results and higher robustness with respect to occlusions.},
booktitle = {Visualization {Transmission} 2012 {Second} {International} {Conference} on {3D} {Imaging}, {Modeling}, {Processing}},
author = {Drost, B. and Ilic, S.},
month = oct,
year = {2012},
keywords = {3D object detection, 3D objects, Cameras, Clutter, Feature extraction, Hough transforms, Hough-like local voting scheme, Image edge detection, Robustness, Solid modeling, Vectors, depth data, edge detection, feature extraction, image matching, industrial applications, inspection, intensity data, localization, manipulation tasks, matching scene, model features, multimodal point pair features, object detection, object silhouette, occlusions, real sequences, robotic applications, rotation-invariant feature, scale-invariant feature, surface appearance},
pages = {9--16},
}
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