Published July 23, 2021 | Version v1
Conference paper Open

cMinMax: A Fast Algorithm to Find the Corners of an N-dimensional Convex Polytope

  • 1. Department of Electrical and Computer Engineering, University of Patras, 2McCormick School of Engineering, Northwestern University
  • 2. Department of Computer Science, Rice University, Houston
  • 3. Department of Electrical and Computer Engineering, University of Patras

Description

During the last years, the emerging field of Augmented & Virtual Reality (AR-VR) has seen tremendous growth. At the same time there is a trend to develop low cost high-quality AR systems where computing power is in demand. Feature points are extensively used in these real-time frame-rate and 3D applications, therefore efficient high-speed feature detectors are necessary. Corners are such special features and often are used as the first step in the marker alignment in Augmented Reality (AR). Corners are also used in image registration and recognition, tracking, SLAM, robot path finding, 2D or 3D object detection and retrieval as well as in linear programming algorithms. Therefore there is a large number of corner detection algorithms but most of them are too computationally intensive for use in real-time applications of any complexity. Many times the border of the image is a convex polygon. For this special, but quite common case, we have developed a specific algorithm, cMinMax. The proposed algorithm is faster, approximately by a factor of 5 compared to the widely used Harris Corner Detection algorithm. In addition is highly parallelizable. The algorithm is suitable for the fast registration of markers in augmented reality systems and in applications where a computationally efficient real time feature detector is necessary. The algorithm can also be extended to N-dimensional polyhedrons.

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Funding

CPSoSaware – Cross-layer cognitive optimization tools & methods for the lifecycle support of dependable CPSoS 871738
European Commission