Dark Synthetic Vision: Lightweight Active Vision to Navigate in the Dark

Kim, Joowan; Jeon, Myung–Hwan; Cho, Younggun; Kim, Ayoung

doi:10.1109/lra.2020.3035137

Cited by 8 publications

(1 citation statement)

References 28 publications

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“…Developing new sensors technologies, such as bio-inspired retinas [5], [6], event-based cameras [7], [8], photon avalanche diode arrays [9], and the heterojunction of different semiconductors [10], is a solution adopted to enhance VBTs in the absence of proper light conditions [11]- [13]. On the other hand, due to their implementation easiness and relative low application costs, image processing techniques, as iterative statistic 3D-points alignment [14], artificial neural networks [15], and different LIDAR data treatments [16], have been a more preferred option that had equally demonstrated to improve VBTs in obscured scenarios.…”

Section: Introductionmentioning

confidence: 99%

Synchronization of a New Light-Flashing Shield With an External-Triggered Camera

Castillo-Zamora,

Negre,

Ingargiola

et al. 2023

IEEE Sens. Lett.

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In this letter, we describe a new light-flashing shield to be used at flash-based imaging or event-based vision tasks performed in environments with poor light conditions. The shield incorporates a multiplexer that permits to set the operation mode, the nominal current, the pulse-width and the trigger sensitivity of up-to 2 high-brightness LEDs by means of a single I2C bus. A trigger conditioning circuit permits to synchronize the LEDs light and an Intel RealSense d455 camera to obtain a set of clear images while the LEDs are illuminated, being this feature the main novelty and contribution of this work in order to provide light on-demand in visual-based tasks performed in environments with poor light conditions. Images obtained during real tests prove the correct synchronization between the light-flashing shield and the camera.

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Section: Introductionmentioning

confidence: 99%

Synchronization of a New Light-Flashing Shield With an External-Triggered Camera

Castillo-Zamora,

Negre,

Ingargiola

et al. 2023

IEEE Sens. Lett.

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AGRI-SLAM: a real-time stereo visual SLAM for agricultural environment

2023

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In this research, we proposed a stereo visual simultaneous localisation and mapping (SLAM) system that efficiently works in agricultural scenarios without compromising the performance and accuracy in contrast to the other state-of-the-art methods. The proposed system is equipped with an image enhancement technique for the ORB point and LSD line features recovery, which enables it to work in broader scenarios and gives extensive spatial information from the low-light and hazy agricultural environment. Firstly, the method has been tested on the standard dataset, i.e., KITTI and EuRoC, to validate the localisation accuracy by comparing it with the other state-of-the-art methods, namely VINS-SLAM, PL-SLAM, and ORB-SLAM2. The experimental results evidence that the proposed method obtains superior localisation and mapping accuracy than the other visual SLAM methods. Secondly, the proposed method is tested on the ROSARIO dataset, our low-light agricultural dataset, and O-HAZE dataset to validate the performance in agricultural environments. In such cases, while other methods fail to operate in such complex agricultural environments, our method successfully operates with high localisation and mapping accuracy.

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A multi-layer fusion image enhancement method for visual odometry under poor visibility scenarios

et al. 2022

International Journal of Applied Earth Observation and Geoinfor

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Dark Synthetic Vision: Lightweight Active Vision to Navigate in the Dark

Cited by 8 publications

References 28 publications

Synchronization of a New Light-Flashing Shield With an External-Triggered Camera

Synchronization of a New Light-Flashing Shield With an External-Triggered Camera

AGRI-SLAM: a real-time stereo visual SLAM for agricultural environment

A multi-layer fusion image enhancement method for visual odometry under poor visibility scenarios

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