Automatic zooming mechanism for capturing object image using high definition fixed camera

Liao, Hsien-Chou; Chen, Po‐Yueh; Lin, Zijun; Lim, Zi-Yi

doi:10.1109/icact.2016.7423424

2016 18th International Conference on Advanced Communication Technology (ICACT) 2016

DOI: 10.1109/icact.2016.7423424

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Automatic zooming mechanism for capturing object image using high definition fixed camera

Hsien-Chou Liao

Po‐Yueh Chen

Zijun Lin

et al.

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2024

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Cited by 2 publications

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A physics-informed deep learning liquid crystal camera with data-driven diffractive guidance

Shi,

Liu,

Zhou

et al. 2024

Commun Eng

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Whether in the realms of computer vision, robotics, or environmental monitoring, the ability to monitor and follow specific targets amidst intricate surroundings is essential for numerous applications. However, achieving rapid and efficient target tracking remains a challenge. Here we propose an optical implementation for rapid tracking with negligible digital post-processing, leveraging an all-optical information processing. This work combines a diffractive-based optical nerual network with a layered liquid crystal electrical addressing architecture, synergizing the parallel processing capabilities inherent in light propagation with liquid crystal dynamic adaptation mechanism. Through a one-time effort training, the trained network enable accurate prediction of the desired arrangement of liquid crystal molecules as confirmed through numerical blind testing. Then we establish an experimental camera architecture that synergistically combines an electrically-tuned functioned liquid crystal layer with materialized optical neural network. With integrating the architecture into optical imaging path of a detector plane, this optical computing camera offers a data-driven diffractive guidance, enabling the identification of target within complex backgrounds, highlighting its high-level vision task implementation and problem-solving capabilities.

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A physics-informed deep learning liquid crystal camera with data-driven diffractive guidance

Shi,

Liu,

Zhou

et al. 2024

Commun Eng

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DMZoomNet: Improving Object Detection Using Distance Information in Intralogistics Environments

Clavero,

Patricio,

García

et al. 2024

IEEE Trans. Ind. Inf.

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Automatic zooming mechanism for capturing object image using high definition fixed camera

Cited by 2 publications

References 5 publications

A physics-informed deep learning liquid crystal camera with data-driven diffractive guidance

A physics-informed deep learning liquid crystal camera with data-driven diffractive guidance

DMZoomNet: Improving Object Detection Using Distance Information in Intralogistics Environments

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