A5051512012- Maritime Navigation and Safety
- Underwater Vehicles and Communication Systems
- Optical measurement and interference techniques
- Advanced Neural Network Applications
- Robotics and Sensor-Based Localization
- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
- Image and Object Detection Techniques
- Underwater Acoustics Research
- Advanced Optical Sensing Technologies
- Domain Adaptation and Few-Shot Learning
- Image Processing Techniques and Applications
- Infrared Target Detection Methodologies
- Advanced Measurement and Detection Methods
- Target Tracking and Data Fusion in Sensor Networks
- Anomaly Detection Techniques and Applications
- Remote Sensing and LiDAR Applications
- Robotic Path Planning Algorithms
University of Ljubljana
2019-2025
The progress of obstacle detection via semantic segmentation on unmanned surface vehicles (USVs) has been significantly lagging behind the developments in related field autonomous cars. reason is lack large curated training datasets from USV domain required for development data-hungry deep CNNs. This paper addresses this issue by presenting MaSTr1325, a marine dataset tailored methods small-sized coastal USVs. contains 1325 diverse images captured over two year span with real USV, covering...
Small-sized unmanned surface vehicles (USV) are coastal water devices with a broad range of applications such as environmental control and surveillance. A crucial capability for autonomous operation is obstacle detection timely reaction collision avoidance, which has been recently explored in the context camera-based visual scene interpretation. Owing to curated datasets, substantial advances interpretation have made related field ground vehicles. However, current maritime datasets do not...
In this paper, we present a method for detecting and tracking waterborne obstacles from an unmanned surface vehicle (USV) the purpose of short-term obstacle avoidance. A stereo camera system provides point cloud scene in front vehicle. The water is estimated by fitting plane to outlying points are further processed find potential obstacles. We propose new algorithm detection that applies fast approximate semantic segmentation filter utilizes external IMU reading constrain orientation. novel...
The 3rd Workshop on Maritime Computer Vision (MaCVi) 2025 addresses maritime computer vision for Unmanned Surface Vehicles (USV) and underwater. This report offers a comprehensive overview of the findings from challenges. We provide both statistical qualitative analyses, evaluating trends over 700 submissions. All datasets, evaluation code, leaderboard are available to public at https://macvi.org/workshop/macvi25.
Camera systems in autonomous vehicles are subject to various sources of anticipated and unanticipated mechanical stress (vibration, rough handling, collisions) real-world conditions. Even moderate changes camera geometry due decalibrate multi-camera corrupt downstream applications like depth perception. We propose an on-the-fly stereo recalibration method applicable vehicles. The is comprised two parts. First, optimization step, external parameters optimized with the goal maximise amount...
Multimodal sensor systems require precise calibration if they are to be used in the field. Due difficulty of obtaining corresponding features from different modalities, such is an open problem. We present a systematic approach for calibrating set cameras with modalities (RGB, thermal, polarization, and dual-spectrum near infrared) regard LiDAR using planar target. Firstly, method single camera proposed. The usable any modality, as long pattern detected. A methodology establishing...
Object grasping is a fundamental challenge in robotics and computer vision, critical for advancing robotic manipulation capabilities. Deformable objects, like fabrics cloths, pose additional challenges due to their non-rigid nature. In this work, we introduce CeDiRNet-3DoF, deep-learning model grasp point detection, with particular focus on cloth objects. CeDiRNet-3DoF employs center direction regression alongside localization network, attaining first place the perception task of ICRA 2023's...
We address the problem of optical decalibration in mobile stereo camera setups, especially context autonomous vehicles. In real world conditions, an system is subject to various sources anticipated and unanticipated mechanical stress (vibration, rough handling, collisions). Mechanical changes geometry between cameras that make up pair, as a consequence, pre-calculated epipolar no longer valid. Our method based on optimization parameters plugs directly into output matching algorithm....