Adaptive moving object segmentation algorithms in cluttered environments

Ivanov, Yuriy; Peleshko, Dmytro; Makoveychuk, Oleksandr; Izonin, Ivan; Malets, Igor; Lotoshunska, Natalia; Batyuk, Danylo

doi:10.1109/cadsm.2015.7230806

Cited by 22 publications

(4 citation statements)

References 2 publications

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“…Videos can also be recorded of the entire ultrasound examination. Real-time tracking and segmentation of moving objects is a subject well known in computer vision [ 88 , 89 , 90 ]. However, tracking selected organs during a USG examination (or in recorded videos) may be difficult, although publications on this subject can be found in the literature [ 91 , 92 ].…”

Section: Challenges and Conclusionmentioning

confidence: 99%

Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review

Ciecholewski

Kassjański

2021

Sensors

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The segmentation of liver blood vessels is of major importance as it is essential for formulating diagnoses, planning and delivering treatments, as well as evaluating the results of clinical procedures. Different imaging techniques are available for application in clinical practice, so the segmentation methods should take into account the characteristics of the imaging technique. Based on the literature, this review paper presents the most advanced and effective methods of liver vessel segmentation, as well as their performance according to the metrics used. This paper includes results available for four imaging methods, namely: computed tomography (CT), computed tomography angiography (CTA), magnetic resonance (MR), and ultrasonography (USG). The publicly available datasets used in research are also presented. This paper may help researchers gain better insight into the available materials and methods, making it easier to develop new, more effective solutions, as well as to improve existing approaches. This article analyzes in detail various segmentation methods, which can be divided into three groups: active contours, tracking-based, and machine learning techniques. For each group of methods, their theoretical and practical characteristics are discussed, and the pros and cons are highlighted. The most advanced and promising approaches are also suggested. However, we conclude that liver vasculature segmentation is still an open problem, because of the various deficiencies and constraints researchers need to address and try to eliminate from the solutions used.

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Section: Challenges and Conclusionmentioning

confidence: 99%

Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review

Ciecholewski

Kassjański

2021

Sensors

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“…It foresees the use of visual markers and Augmented Reality (AR) to localize a specific Point of Interest (POI) in the domestic environment and then drive the wheelchair there. The POI detection is performed by searching in the RGB frame through the ArUco library, something similar to [36,37] who analyze and use the segmentation algorithms in video-surveillance systems and cluttered environments.…”

Section: Semi-autonomous Drivementioning

confidence: 99%

RoboEye, an Efficient, Reliable and Safe Semi-Autonomous Gaze Driven Wheelchair for Domestic Use

et al. 2021

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Any severe motor disability is a condition that limits the ability to interact with the environment, even the domestic one, caused by the loss of control over one’s mobility. This work presents RoboEYE, a power wheelchair designed to allow users to move easily and autonomously within their homes. To achieve this goal, an innovative, cost-effective and user-friendly control system was designed, in which a non-invasive eye tracker, a monitor, and a 3D camera represent some of the core elements. RoboEYE integrates functionalities from the mobile robotics field into a standard power wheelchair, with the main advantage of providing the user with two driving options and comfortable navigation. The most intuitive and direct modality foresees the continuous control of frontal and angular wheelchair velocities by gazing at different areas of the monitor. The second, semi-autonomous modality allows navigation toward a selected point in the environment by just pointing and activating the wished destination while the system autonomously plans and follows the trajectory that brings the wheelchair to that point. The purpose of this work was to develop the control structure and driving interface designs of the aforementioned driving modalities taking into account also uncertainties in gaze detection and other sources of uncertainty related to the components to ensure user safety. Furthermore, the driving modalities, in particular the semi-autonomous one, were modeled and qualified through numerical simulations and experimental verification by testing volunteers, who are regular users of standard electric wheelchairs, to verify the efficiency, reliability and safety of the proposed system for domestic use. RoboEYE resulted suitable for environments with narrow passages wider than 1 m, which is comparable with a standard domestic door and due to its properties with large commercialization potential.

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“…Video processing technologies such as target tracking [1,2], target detection [3,4], and moving target segmentation [5,6] have made great progress, with related applications continuing to emerge. Among them, target tracking has been widely used in intelligent video surveillance, modern military, and intelligent visual navigation equipment.…”

Section: Introductionmentioning

confidence: 99%

Dim and Small Target Tracking Using an Improved Particle Filter Based on Adaptive Feature Fusion

et al. 2022

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Particle filters have been widely used in dim and small target tracking, which plays a significant role in navigation applications. However, their characteristics, such as difficulty of expressing features for dim and small targets and lack of particle diversity caused by resampling, lead to a considerable negative impact on tracking performance. In the present paper, we propose an improved resampling particle filter algorithm based on adaptive multi-feature fusion to address the drawbacks of particle filters for dim and small target tracking and improve the tracking performance. We first establish an observation model based on the adaptive fusion of the features of the weighted grayscale intensity, edge information, and wavelet transform. We then generate new particles based on residual resampling by combining the target position in the previous frame and the particles in the current frame with higher weights, with the tracking accuracy and particle diversity improving simultaneously. The experimental results demonstrate that our proposed method achieves a high tracking performance with a distance accuracy of 77.2% and a running speed of 106 fps, respectively, meaning that it will have a promising prospect in dim and small target tracking applications.

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Adaptive moving object segmentation algorithms in cluttered environments

Cited by 22 publications

References 2 publications

Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review

Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review

RoboEye, an Efficient, Reliable and Safe Semi-Autonomous Gaze Driven Wheelchair for Domestic Use

Dim and Small Target Tracking Using an Improved Particle Filter Based on Adaptive Feature Fusion

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