Incremental Model Selection for Detection and Tracking of Planar Surfaces

Prankl, Johann; Zillich, Michael; Leibe, Bastian; Vincze, Markus

doi:10.5244/c.24.87

Cited by 8 publications

(8 citation statements)

References 28 publications

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“…These approaches have to create plane hypotheses independently of each other and thus it is not possible to restrict the search space, which leads to higher computational complexity. Our method is most similar to the approach by Prankl et al [14], who propose incremental model selection based on the MDL principle to overcome these drawbacks.…”

Section: A Related Workmentioning

confidence: 91%

3D piecewise planar object model for robotics manipulation

Prankl

Zillich

Vincze

2011

2011 IEEE International Conference on Robotics and Automation

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Man-made environments are abundant with planar surfaces which have attractive properties for robotics manipulation tasks and are a prerequisite for a variety of vision tasks. This work presents automatic on-line 3D object model acquisition assuming a robot to manipulate the object. Objects are represented with piecewise planar surfaces in a spatio-temporal graph. Planes once detected as homographies are tracked and serve as priors in subsequent images. After reconstruction of the planes the 3D motion is analyzed and initial object hypotheses are created. In case planes start moving independently a split event is triggered, the spatio-temporal object graph is traced back and visible planes as well as occluded planes are assigned to the most probable split object. The novelty of this framework is to formalize Multi-body Structure-and-Motion (MSaM), that is, to segment interest point tracks into different rigid objects and compute the multiple-view geometry of each object, with Minimal Description Length (MDL) based on model selection of planes in an incremental manner. Thus, object models are built from planes, which directly can be used for robotic manipulation.

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Section: A Related Workmentioning

confidence: 91%

3D piecewise planar object model for robotics manipulation

Prankl

Zillich

Vincze

2011

2011 IEEE International Conference on Robotics and Automation

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“…In this paper, we show how to extend this method to produce consistent plane models over long video sequences. Recently, [17] proposes a model selection method for multiple-frame plane detection using the Minimal Description Length (MDL) principle. While it focuses on discovering multiple plane models simultaneously, its robustness to gross outliers is unknown.…”

Section: Related Workmentioning

confidence: 99%

Robust plane-based structure from motion

Zhou

Jin

2012

2012 IEEE Conference on Computer Vision and Pattern Recognition

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We introduce a new approach to structure and motion recovery directly from one or more large planes in the scene. When such a plane exists, we demonstrate how to automatically detect and track it robustly and consistently over a long video sequence, and how to efficiently self-calibrate the camera using the homographies induced by this plane. We build a complete structure from motion system which does not use any additional off-the-plane information about the scene, and show its advantage over conventional systems in handling two important issues which often occur in real world videos, namely, the plane degeneracy and the dynamic foreground problems. Experimental results on a variety of real video sequences verify the effectiveness and efficiency of our system.

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“…Furthermore, we focus on the temporal consistency of the representation. Some attempts towards detecting and tracking 3D planar representations over time have been made, but from 2D image correspondences, as proposed in [24,21].…”

Section: Related Workmentioning

confidence: 99%

Tracking planes with Time of Flight cameras and J-linkage

Schwarz¹,

Mateus²,

Lallemand³

et al. 2011

2011 IEEE Workshop on Applications of Computer Vision (WACV)

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In this paper, we propose a method for detection and tracking of multiple planes in sequences of Time of Flight (ToF) depth images. Our approach extends the recent J-linkage algorithm for estimation of multiple model instances in noisy data to tracking. Instead of randomly selecting plane hypotheses in every image, we propagate plane hypotheses through the sequence of images, resulting in a significant reduction of computational load in every frame. We also introduce a multi-pass scheme that allows detecting and tracking planes of varying spatial extent along with their boundaries. Our qualitative and quantitative evaluation shows that the proposed method can robustly detect planes and consistently track the hypotheses through sequences of ToF images.

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Incremental Model Selection for Detection and Tracking of Planar Surfaces

Cited by 8 publications

References 28 publications

3D piecewise planar object model for robotics manipulation

3D piecewise planar object model for robotics manipulation

Robust plane-based structure from motion

Tracking planes with Time of Flight cameras and J-linkage

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