Distance estimation for marine vehicles using a monocular video camera

Gladstone, Ran; Moshe, Yair; Barel, Avihai; Shenhav, Elior

doi:10.1109/eusipco.2016.7760680

Cited by 15 publications

(11 citation statements)

References 13 publications

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“…Otherwise, monocular distance estimation methods exploit the camera movement, such as in [30], but these methods can only estimate the distance to static targets. More recently, methods which do not require camera movement have started to emerge, such as [31], [32].…”

Section: Visual Sensorsmentioning

confidence: 99%

Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review

Thombre

Zhao

Ramm-Schmidt³

et al. 2022

IEEE Trans. Intell. Transport. Syst.

151

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Autonomous ships are expected to improve the level of safety and efficiency in future maritime navigation. Such vessels need perception for two purposes: to perform autonomous situational awareness and to monitor the integrity of the sensor system itself. In order to meet these needs, the perception system must fuse data from novel and traditional perception sensors using Artificial Intelligence (AI) techniques. This article overviews the recognized operational requirements that are imposed on regular and autonomous seafaring vessels, and then proceeds to consider suitable sensors and relevant AI techniques for an operational sensor system. The integration of four sensors families is considered: sensors for precise absolute positioning (Global Navigation Satellite System (GNSS) receivers and Inertial Measurement Unit (IMU)), visual sensors (monocular and stereo cameras), audio sensors (microphones), and sensors for remotesensing (RADAR and LiDAR). Additionally, sources of auxiliary data, such as Automatic Identification System (AIS) and external data archives are discussed. The perception tasks are related to well-defined problems, such as situational abnormality detection, vessel classification, and localization, that are solvable using AI techniques. Machine learning methods, such as deep learning and Gaussian processes, are identified to be especially relevant for these problems. The different sensors and AI techniques are characterized keeping in view the operational requirements, and some example state-of-the-art options are compared based on accuracy, complexity, required resources, compatibility and adaptability to maritime environment, and especially towards practical realization of autonomous systems.

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Section: Visual Sensorsmentioning

confidence: 99%

Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review

Thombre

Zhao

Ramm-Schmidt³

et al. 2022

IEEE Trans. Intell. Transport. Syst.

151

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“…Horizon information is used in some object detection approaches and for the reduction of false positives for a given object detection rate (Jeong et al, 2018a). Also, it is used for distance prediction of another object to the camera (Gladstone et al, 2016) or for maritime target detection and tracking in infrared images (Jian and Wen, 2019). We can distinguish three main approaches for horizon detection: projection-based, region-based and hybrid.…”

Section: Horizon Detection In Maritime Zone Video Surveillancementioning

confidence: 99%

“…Maritime video surveillance may take place from a small surface-vehicle (manned or unmanned)mounted camera or buoy in line with the water to static landbased cameras or aerial surveillance from drones. According to (Gladstone et al, 2016;Bloisi et al, 2017;Vujović and Kuzmanić, 2018), maritime surveillance systems have to overcome a set of challenges:…”

Section: Introductionmentioning

confidence: 99%

An Overview on Horizon Detection Methods in Maritime Video Surveillance

2020

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The interest in video surveillance has been increasing in the fields of maritime industry in the past decade. Maritime transportation system is a vital part of the world’s economy and the extent of global ship traffic is increasing. This trend encourages the development of intelligent surveillance systems in the maritime zone. The development of intelligent surveillance systems includes sensor and data fusion, which incorporates multispectral and multisensory data to replace the traditional approach with radars only. Video cameras are widely used since they capture images of greater resolution than most sensor systems. Also, combined with video analytics they provide sensors with high capability, complex pattern recognition analytics, and multiple variables for the decision making process. In this paper, an overview of a small part of the system is presented – horizon detection.

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“…Lane detection was used in their work to compute the vanishing point. Horizon line detection was conducted in work [28]. Then the distance from the vehicle is calculated by the pixel distance from the horizon line.…”

Section: Related Workmentioning

confidence: 99%