Structure from Motion Using Bio-Inspired Intelligence Algorithm and Conformal Geometric Algebra

Structure from Motion algorithms offer good advantages, such as extract 3D information in monocular systems and structures estimation as shown in Hartley & Zisserman for numerous applications, for instance; augmented reality, autonomous navigation, motion capture, remote sensing and object recognition among others. Nevertheless, this algorithm suffers some weaknesses in precision. In the present work, we extent the proposal in Arana-Daniel, Villasenor, Lopez-Franco, & Alanis that presents a new strategy using bio-inspired intelligence algorithm and Conformal Geometric Algebra, based in the object mapping paradigm, to overcome the accuracy problem in two-view Structure form motion algorithms. For this instance, we include two new experiments and the inclusion of the circle entity; the circle carries stronger information about its motion than other geometric entities, as we will show.

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