Jing Zhang^1,2, Xin Qi^3,*, San Hlaing Myint³, Zheng Wen⁴

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2807-2824, 2021, DOI:10.32604/cmc.2021.017410 - 13 April 2021

Abstract With increasingly more smart cameras deployed in infrastructure and commercial buildings, 3D reconstruction can quickly obtain cities’ information and improve the efficiency of government services. Images collected in outdoor hazy environments are prone to color distortion and low contrast; thus, the desired visual effect cannot be achieved and the difficulty of target detection is increased. Artificial intelligence (AI) solutions provide great help for dehazy images, which can automatically identify patterns or monitor the environment. Therefore, we propose a 3D reconstruction method of dehazed images for smart cities based on deep learning. First, we propose a… More >

Nancy Arana-Daniel, Carlos Villaseñor, Carlos López-Franco, Alma Y. Alanís, Roberto Valencia-Murillo

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 461-467, 2018, DOI:10.1080/10798587.2017.1299356

Abstract 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, Villaseñor, López-Franco, & Alanís 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 More >