Computing 3D From-Region Visibility Using Visibility Integrity

Jixuan Zhi, Yue Hao, Christopher Vo, Marco Morales and Jyh-Ming Lien


Computing from-region visibility is a fundamental problem that involves determining the visible part of a 2D or 3D space from a given region. It is not well studied if regions are moving such as moving crowds.

We propose an idea called Visibility integrity, which is used for measuring the similarity between the visibilities of regions. We draw samples and computes point-to-point visibilities to approximate the from-region visibility of moving regions, called group visibility.


Based on the new idea of visibility integrity, we show that the visibility-integrity roadmap, a data structure that partitions space into zones, can be used to solve group visibility and the group following problems in 3D.


The group following problem involves finding a sequence of positions and orientations of the camera to maximize the number of visible targets during a specified period of time. To find the position of the camera, we first predict the target position, then assign the position to a visibility integrity region, finally predict and evaluate camera positions by querying visibility-integrity roadmap.



The video shows the concept of Visibility integrity (VI), how Visibility integrity partitions the space and a planning algorithm for the camera to maintain visibility of group targets by querying the visibility-integrity roadmap.


Computing 3-D From-Region Visibility Using Visibility Integrity, Zhi, Jixuan and Hao, Yue and Vo, Christopher and Morales, Marco and Lien, Jyh-Ming, IEEE Robotics and Automation Letters (RA-L) and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019
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Computer Science @ George Mason University