Multi-resolution feature fusion DCF (Discriminative Correlation Filter) methods have significantly advanced the object tracking performance. However, careless choice and fusion of sample features make the algorithm susceptible to interference, leadin...
Feature tracking in image collections significantly affects the efficiency and accuracy of Structure from Motion (SFM). Insufficient correspondences may result in disconnected structures and incomplete components, while the redundant correspondences...
In the field of drone-based object tracking, utilization of the infrared modality can improve the robustness of the tracker in scenes with severe illumination change and occlusions and expand the applicable scene of the drone object tracking task. In...
In this paper, we build on past efforts with regard to the implementation of an efficient feature tracking algorithm for the mass processing of satellite images. This generic open-source feature tracking routine can be applied to any type of imagery...
Object tracking is one of the most challenging problems in the field of computer vision. In challenging object tracking scenarios such as illumination variation, occlusion, motion blur and fast motion, existing algorithms can present decreased perfor...
Moving object tracking techniques using machine and deep learning require large datasets for neural model training. New strategies need to be invented that utilize smaller data training sizes to realize the impact of large-sized datasets. However, cu...
Siamese network-based trackers have developed rapidly in the field of visual object tracking recently. Many Siamese network-based trackers currently in use rely on result fusion to combine the classification result map and regression result map. Howe...
Establishing an accurate and robust feature fusion mechanism is key to enhancing the tracking performance of single-object trackers based on a Siamese network. However, the output features of the depth-wise cross-correlation feature fusion module in...
Efficient multi-object tracking (MOT) in satellite videos is crucial for numerous applications, ranging from surveillance to environmental monitoring. Existing methods often struggle with effectively exploring the correlation and contextual cues inhe...
Sea ice drift detection has the key role of global climate analysis and waterway planning. The ability to detect sea ice drift in real-time also contributes to the safe navigation of ships and the prevention of offshore oil platform accidents. In thi...
This paper investigates the application of feature tracking algorithms as an alternative data processing method for laser speckle instrumentation. The approach is capable of determining both the speckle pattern translation and rotation and can theref...
Achieving efficient and accurate feature tracking on event cameras is a fundamental step for practical high-level applications, such as simultaneous localization and mapping (SLAM) and structure from motion (SfM) and visual odometry (VO) in GNSS (Glo...
At present, feature-based 3D reconstruction and tracking technology is widely applied in the medical field. In minimally invasive surgery, the surgeon can achieve three-dimensional reconstruction through the images obtained by the endoscope in the hu...
The fusion tracking of RGB and thermal infrared image (RGBT) is paid wide attention to due to their complementary advantages. Currently, most algorithms obtain modality weights through attention mechanisms to integrate multi-modalities information. T...
This paper proposes a tracking method combining feature enhancement and template update, aiming to solve the problems of existing trackers lacking global information attention, weak feature characterization ability, and not being well adapted to the...
Object tracking is a computer vision task deemed necessary for high-level intelligent decision-making algorithms. Researchers have merged different object tracking techniques and discovered a new class of hybrid algorithms that is based on embedding...
With the rapid advancement of hyperspectral imaging technology, hyperspectral object tracking (HOT) has become a research hotspot in the field of remote sensing. Advanced HOT methods have been continuously proposed and validated on scarce datasets in...
Pedestrian tracking is an important research content in the field of computer vision. Tracking is achieved by predicting the position of a specific pedestrian in each frame of a video. Pedestrian tracking methods include neural network-based methods...
Aiming at the problem of poor robustness and the low effectiveness of target tracking in complex scenes by using single color features, an object-tracking algorithm based on dual color feature fusion via dimension reduction is proposed, according to...
Siamese network-based trackers are broadly applied to solve visual tracking problems due to its balanced performance in terms of speed and accuracy. Tracking desired objects in challenging scenarios is still one of the fundamental concerns during vis...
Recently, correlation filter (CF)-based tracking algorithms have attained extensive interest in the field of unmanned aerial vehicle (UAV) tracking. Nonetheless, existing trackers still struggle with selecting suitable features and alleviating the mo...
In spinal surgery, surgical navigation is an essential tool for safe intervention, including the placement of pedicle screws without injury to nerves and blood vessels. Commercially available systems typically rely on the tracking of a dynamic refere...
Most existing object tracking research focuses on pedestrians and autonomous driving while ignoring sports scenes. When general object tracking models are used for ball tracking, there are often problems, such as detection omissions due to small obje...
Multi-camera video surveillance has been widely applied in crowd statistics and analysis in smart city scenarios. Most existing studies rely on appearance or motion features for cross-camera trajectory tracking, due to the changing asymmetric perspec...
Animal tracking is crucial for understanding migration, habitat selection, and behavior patterns. However, challenges in video data acquisition and the unpredictability of animal movements have hindered progress in this field. To address these challe...
With the rise of general models, transformers have been adopted in visual object tracking algorithms as feature fusion networks. In these trackers, self-attention is used for global feature enhancement. Cross-attention is applied to fuse the features...
To boost the robustness of the traditional particle-filter-based tracking algorithm under complex scenes and to tackle the drift problem that is caused by the fast moving target, an improved particle-filter-based tracking algorithm is proposed. First...
Statistical measurements of eye movement-specific properties, such as fixations, saccades, blinks, or pupil dilation, are frequently utilized as input features for machine learning algorithms applied to eye tracking recordings. These characteristics...
There is a well-known problem of video sequence analysis when it is necessary to identify and localize areas of abnormal movement of objects. This is necessary to attract the attention of the operator in the process of work or when analyzing the arch...
Driven by the rapid advancement of Unmanned Aerial Vehicle (UAV) technology, the field of UAV object tracking has witnessed significant progress. This study introduces an innovative single-stream UAV tracking architecture, dubbed NT-Track, which is d...
The TransT object tracking algorithm, built on Transformer architecture, effectively integrates deep feature extraction with attention mechanisms, thereby enhancing the stability and accuracy of the algorithm. However, this algorithm exhibits insuffi...
In this paper, a novel online learning-based tracker is presented for the unmanned aerial vehicle (UAV) in different types of tracking applications, such as pedestrian following, automotive chasing, and building inspection. The presented tracker uses...
The scanning speed of atomic force microscopes continues to advance with some current commercial microscopes achieving on the order of one frame per second and at least one reaching 10 frames per second. Despite the success of these instruments, even...
Multiple object tracking (MOT) in videos captured by unmanned aerial vehicle (UAV) is a fundamental aspect of computer vision. Recently, the one-shot tracking paradigm integrates the detection and re-identification (ReID) tasks, striking a balance be...
Eye Tracking (ET) parameters, as physiological signals, are widely applied in emotion recognition and show promising performance. However, emotion recognition relying on ET parameters still faces several challenges: (1) insufficient extraction of tem...
High-frequency surface wave radar (HFSWR) with a small aperture suffers from limited azimuth resolution, which often leads to association errors and trajectory fragmentation in complex scenarios involving sea clutter and intersecting target tracks. T...
Crowd anomaly detection is crucial in enhancing surveillance and crowd management. This paper proposes an efficient approach that combines spatial and temporal visual descriptors, sparse feature tracking, and neural networks for efficient crowd anoma...
Multi-target tracking (MTT) is one of the most important functions of radar systems. Traditional multi-target tracking methods based on data association convert multi-target tracking problems into single-target tracking problems. When the number of t...
With the revolutionary development of cloud computing and internet of things, the integration and utilization of “big data” resources is a hot topic of the artificial intelligence research. Face recognition technology information has the...
In large bowel investigations using endoscopic capsules and upon detection of significant findings, physicians require the location of those findings for a follow-up therapeutic colonoscopy. To cater to this need, we propose a model based on tracking...
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 partic...
This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which mak...
Considering the detrimental effects of dyslexia on academic performance and its common occurrence, developing tools for dyslexia detection, monitoring, and treatment poses a task of significant priority. The research performed in this paper was focus...
Following the growing availability of low-cost, commercially available unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on object tracking using videos recorded from UAVs. However, tracking from UAV videos poses many...
To address the problem that the performance of hyperspectral target tracking will be degraded when facing background clutter, this paper proposes a novel hyperspectral target tracking algorithm based on the deep edge convolution feature (DECF) and an...
Entomological radar is an effective means of monitoring insect migration, and can realize long-distance and large-scale rapid monitoring. The stable tracking of individual insect targets is the basic premise underlying the identification of insect sp...
Visual object tracking is a fundamental task in computer vision that requires estimating the position and scale of a target object in a video sequence. However, scale variation is a difficult challenge that affects the performance and robustness of m...
A problem of tracking surface shape-shifting extended target by using gray scale pixels on optical image is considered. The measurement with amplitude information (AI) is available to the proposed method. The target is regarded as a convex hemispheri...
Three-dimensional (3D) single-object tracking (3D SOT) is a fundamental yet not well-solved problem in 3D vision, where the complexity of feature matching and the sparsity of point clouds pose significant challenges. To handle abrupt changes in appea...
The discriminative object tracking system for unmanned aerial vehicles (UAVs) is widely used in numerous applications. While an ample amount of research has been carried out in this domain, implementing a low computational cost algorithm on a UAV onb...
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