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Topic Review
Vision-Based Vibration Monitoring
Contactless structural monitoring has in recent years seen a growing number of applications in civil engineering. Indeed, the elimination of physical installations of sensors is very attractive, especially for structures that might not be easily or safely accessible, yet requiring the experimental evaluation of their conditions, for example following extreme events such as strong earthquakes, explosions, and floods. Among contactless technologies, vision-based monitoring is possibly the solution that has attracted most of the interest of civil engineers, given that the advantages of contactless monitoring can be potentially obtained thorough simple and low-cost consumer-grade instrumentations.
  • 1.1K
  • 07 Jan 2021
Topic Review
Vision-Based Structural Vibration Tracking Using a Digital Camera
Computer-vision-based target tracking can be applied to structural vibration monitoring, but current target tracking methods suffer from noise in digital image processing. A new target-tracking method based on the sparse optical flow technique is introduced to improve the accuracy in tracking the target, especially when the target has a large displacement. The proposed method utilizes the ORB technique to maintain a variety of keypoints and combines the multi-level strategy with a sparse optical flow algorithm to search the keypoints with a large motion vector for tracking. Then, an outlier removal method based on Hamming distance and interquartile range (IQR) score is introduced to minimize the error. The proposed target tracking method is verified through a lab experiment---a three-story shear building structure subjected to various harmonic excitations. It is compared with existing sparse optical flow-based target tracking methods and target tracking methods based on three other types of techniques, i.e., feature matching, dense optical flow, and template matching. The results show that the performance of target tracking is greatly improved through the use of a multi-level strategy and the proposed outlier removal method. The proposed sparse optical flow-based target tracking method achieves the best accuracy compared to other existing target tracking methods.
  • 570
  • 01 Dec 2022
Topic Review
Vision-Based Robotic Applications
Being an emerging technology, robotic manipulation has encountered tremendous advancements due to technological developments starting from using sensors to artificial intelligence. Over the decades, robotic manipulation has advanced in terms of the versatility and flexibility of mobile robot platforms. Thus, robots are now capable of interacting with the world around them. To interact with the real world, robots require various sensory inputs from their surroundings, and the use of vision is rapidly increasing, as vision is unquestionably a rich source of information for a robotic system.
  • 564
  • 08 Jan 2023
Topic Review
Vision-Based Pose Estimation of Non-Cooperative Target
In the realm of non-cooperative space security and on-orbit service, a significant challenge is accurately determining the pose of abandoned satellites using imaging sensors. Traditional methods for estimating the position of the target encounter problems with stray light interference in space, leading to inaccurate results.
  • 272
  • 18 Dec 2023
Topic Review
Vision-Based Methods for Food and Fluid Intake Monitoring
Food and fluid intake monitoring are essential for reducing the risk of dehydration, malnutrition, and obesity. The existing research has been preponderantly focused on dietary monitoring, while fluid intake monitoring, on the other hand, is often neglected. Food and fluid intake monitoring can be based on wearable sensors, environmental sensors, smart containers, and the collaborative use of multiple sensors. Vision-based intake monitoring methods have been widely exploited with the development of visual devices and computer vision algorithms. Vision-based methods provide non-intrusive solutions for monitoring. They have shown promising performance in food/beverage recognition and segmentation, human intake action detection and classification, and food volume/fluid amount estimation. However, occlusion, privacy, computational efficiency, and practicality pose significant challenges.
  • 377
  • 18 Jul 2023
Topic Review
Vision-Based Human Action Recognition Field
Artificial intelligence’s rapid advancement has enabled various applications, including intelligent video surveillance systems, assisted living, and human–computer interaction. These applications often require one core task: video-based human action recognition.
  • 357
  • 23 Apr 2023
Topic Review
Vision-Based Gait Recognition
Identifying people’s identity by using behavioral biometrics has attracted many researchers’ attention in the biometrics industry. Gait is a behavioral trait, whereby an individual is identified based on their walking style. Over the years, gait recognition has been performed by using handcrafted approaches. Due to several covariates’ effects, the competence of the approach has been compromised. Deep learning is an emerging algorithm in the biometrics field, which has the capability to tackle the covariates and produce highly accurate results. 
  • 482
  • 12 Aug 2022
Topic Review
Vision-Based Flying Obstacle Detection for Avoiding Midair Collisions
See and avoid is a basic procedure that pilots must learn and apply during flight. Various technologies have been introduced to avoid midair collisions, but accidents still occur because they are neither mandatory in all airspaces nor suitable for all aircraft.
  • 199
  • 26 Oct 2023
Topic Review
Vision-Based Fall Detection Systems
Vision-based fall detection systems have experienced fast development over the last years. To determine the course of its evolution and help new researchers, the main audience of this paper, a comprehensive revision of all published articles in the main scientific databases regarding this area during the last five years has been made. After a selection process, detailed in the Materials and Methods Section, eighty-one systems were thoroughly reviewed. Their characterization and classification techniques were analyzed and categorized. Their performance data were also studied, and comparisons were made to determine which classifying methods best work in this field. The evolution of artificial vision technology, very positively influenced by the incorporation of artificial neural networks, has allowed fall characterization to become more resistant to noise resultant from illumination phenomena or occlusion. The classification has also taken advantage of these networks, and the field starts using robots to make these systems mobile. However, datasets used to train them lack real-world data, raising doubts about their performances facing real elderly falls. In addition, there is no evidence of strong connections between the elderly and the communities of researchers.
  • 707
  • 17 Feb 2021
Topic Review
Vision-Based Defect Inspection for Sewer Pipes
Underground sewerage systems (USSs) are a vital part of public infrastructure that contributes to collecting wastewater or stormwater from various sources and conveying it to storage tanks or sewer treatment facilities. A healthy USS with proper functionality can effectively prevent urban waterlogging and play a positive role in the sustainable development of water resources. Since it was first introduced in the 1960s, computer vision (CV) has become a mature technology that is used to realize promising automation for sewer inspections.
  • 992
  • 28 Apr 2022
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