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- research-articleJune 2024
Object Tracking Algorithm based on Transformer with Temporal Contexts
AIPR '23: Proceedings of the 2023 6th International Conference on Artificial Intelligence and Pattern RecognitionSeptember 2023, Pages 564–570https://doi.org/10.1145/3641584.3641668Most existing trackers rely solely on current frame information for object tracking. As a result, phenomena such as drifting or tracking failures occur when complex situations arise, such as out-of-view, fast motion and motion blur. To address these ...
- research-articleJune 2024
Lightweight Object Detection-Tracking using Deep Feature Distillation
ICMLC '24: Proceedings of the 2024 16th International Conference on Machine Learning and ComputingFebruary 2024, Pages 287–291https://doi.org/10.1145/3651671.3651688Object detection and tracking are critical and fundamental problems in machine vision task. In this paper, an object detection and tracking method is proposed based on deep feature distillation. Particularly, an adaptive unsupervised Teacher-Student ...
- articleJune 2024
Performance Study of Object Tracking with Multiple Kalman Filters in Autonomous Driving Systems
ACM SIGAda Ada Letters (SIGADA), Volume 43, Issue 2December 2023, Pages 89–93https://doi.org/10.1145/3672359.3672374Object tracking is an important and central aspect of autonomous driving, as it underlies the obstacle detection and avoidance systems of any type of autonomous vehicles. A widely used method for tracking is based on Kalman filters, both for linear and ...
- short-paperJune 2024
Poster: Towards Acoustic-Based Tagless Object Tracking with Smartwatches
MOBISYS '24: Proceedings of the 22nd Annual International Conference on Mobile Systems, Applications and ServicesJune 2024, Pages 664–665https://doi.org/10.1145/3643832.3661411Locating and replacing lost items can be a time-consuming and demanding task, requiring a significant amount of resources. While tag-based object tracking systems like Apple's AirTags are suggested, attaching tags on objects can compromise their ...
- research-articleMay 2024
RainyTrack: Enhancing Object Tracking in Adverse Weather Conditions with Siamese Networks
ICIGP '24: Proceedings of the 2024 7th International Conference on Image and Graphics ProcessingJanuary 2024, Pages 308–315https://doi.org/10.1145/3647649.3647698Object tracking is a critical task in the field of computer vision, playing a significant role in many practical applications. However, in complex rainy conditions, existing object tracking methods often perform poorly. This is due to rain introducing ...
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- research-articleApril 2024
A machine learning pipeline for extracting decision-support features from traffic scenes1
- Vitor A. Fraga,
- Lincoln V. Schreiber,
- Marco Antonio C. da Silva,
- Rafael Kunst,
- Jorge L.V. Barbosa,
- Gabriel de O. Ramos,
- Ana L.C. Bazzan,
- Ivana Dusparic,
- Marin Lujak,
- Giuseppe Vizzari
Traffic systems play a key role in modern society. However, these systems are increasingly suffering from problems, such as congestions. A well-known way to efficiently reduce this kind of problem is to perform traffic light control intelligently through ...
- research-articleApril 2024
A Study on the energy-efficiency of the Object Tracking Algorithms in Edge Devices
UCC '23: Proceedings of the IEEE/ACM 16th International Conference on Utility and Cloud ComputingDecember 2023, Article No.: 29, Pages 1–6https://doi.org/10.1145/3603166.3632541Integrating machine learning techniques with edge computing devices powered by Graphics Processing Units and Tensor Processing Units has revolutionized computer vision and real-time tracking systems. Object detection and motion tracking, crucial for ...
- research-articleJanuary 2024
Object detection and tracking using TSM-EFFICIENTDET and JS-KM in adverse weather conditions
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology (JIFS), Volume 46, Issue 12024, Pages 2399–2413https://doi.org/10.3233/JIFS-233623An efficient model to detect and track the objects in adverse weather is proposed using Tanh Softmax (TSM) EfficientDet and Jaccard Similarity based Kuhn-Munkres (JS-KM) with Pearson-Retinex in this paper. The noises were initially removed using ...
- research-articleDecember 2023
Spatial feature embedding for robust visual object tracking
IET Computer Vision (CVI2), Volume 18, Issue 4June 2024, Pages 540–556https://doi.org/10.1049/cvi2.12263AbstractRecently, the offline‐trained Siamese pipeline has drawn wide attention due to its outstanding tracking performance. However, the existing Siamese trackers utilise offline training to extract ‘universal’ features, which is insufficient to ...
The anchor‐free Siamese tracking method is prone to ‘target‐like’ classification responses in areas with backgrounds clutter and similar distractors, affecting tracking accuracy. The authors propose a spatial remapping network that provide more ...
- research-articleDecember 2023
Cell Tracking via Reinforcement Learning with Microscopic Image Simulator
ICBET '23: Proceedings of the 2023 13th International Conference on Biomedical Engineering and TechnologyJune 2023, Pages 16–22https://doi.org/10.1145/3620679.3620682Recent advances in optical microscopy and fluorescent protein technology have made it possible to record movies of cells over time while keeping them alive. Cell tracking is necessary to extract and analyze cell dynamics from these movies. Tracking-by-...
- demonstrationOctober 2023
Demonstrating BrightMarkers: Fluorescent Tracking Markers Embedded in 3D Printed Objects
- Mustafa Doga Dogan,
- Raul Garcia-Martin,
- Patrick William Haertel,
- Jamison John O'Keefe,
- Raul Sanchez-Reillo,
- Stefanie Mueller
UIST '23 Adjunct: Adjunct Proceedings of the 36th Annual ACM Symposium on User Interface Software and TechnologyOctober 2023, Article No.: 53, Pages 1–3https://doi.org/10.1145/3586182.3615977In this demonstration, we showcase BrightMarker, a fabrication method that uses fluorescent filaments to embed easily trackable markers in 3D printed color objects. By employing an infrared-fluorescent filament that emits light at a wavelength higher ...
- research-articleOctober 2023
IoUNet++: Spatial cross‐layer interaction‐based bounding box regression for visual tracking
IET Computer Vision (CVI2), Volume 18, Issue 1February 2024, Pages 177–189https://doi.org/10.1049/cvi2.12235AbstractAccurate target prediction, especially bounding box estimation, is a key problem in visual tracking. Many recently proposed trackers adopt the refinement module called IoU predictor by designing a high‐level modulation vector to achieve bounding ...
This paper proposes a novel IoU predictor (IoUNet++) for visual tracking that uses multi‐layer fused spatial template features and depthwise separable convolutional correlations to achieve more accurate bounding box estimation. The tracker improved by ...
- ArticleOctober 2023
SpikeBALL: Neuromorphic Dataset for Object Tracking
Advances in Computational IntelligenceJun 2023, Pages 641–652https://doi.org/10.1007/978-3-031-43078-7_52AbstractMost of widely used datasets are not suitable for Spiking Neural Networks (SNNs) due to the need to encode the static data into spike trains and then put them into the network. In addition, the majority of these datasets have been generated to ...
- research-articleSeptember 2023
Scene flow estimation from 3D point clouds based on dual‐branch implicit neural representations
IET Computer Vision (CVI2), Volume 18, Issue 2March 2024, Pages 210–223https://doi.org/10.1049/cvi2.12237AbstractRecently, online optimisation‐based scene flow estimation has attracted significant attention due to its strong domain adaptivity. Although online optimisation‐based methods have made significant advances, the performance is far from ...
The authors introduce a dual‐branch MLP‐based architecture to encode implicit scene representations from a source 3D point cloud, which can additionally synthesise a target 3D point cloud. Thus, the mapping function between the source and synthesised ...
- research-articleAugust 2023
Real-Time Object Localization for Human-Robot Handover
- Sadjad Asghari-Esfeden,
- Garrit Strenge,
- Kyle Lockwood,
- Yunus Bicer,
- Tales Imbiriba,
- Mariusz Furmanek,
- Mathew Yarossi,
- Eugene Tunik,
- Taskin Padir,
- Deniz Erdogmus
PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive EnvironmentsJuly 2023, Pages 42–46https://doi.org/10.1145/3594806.3594854Human-robot interaction in a physical world like handover of objects requires perception systems to be efficient in localizing the object of interest. In this paper we propose an approach to estimate the location of the object with a low-cost RGB ...
- research-articleJune 2023
Robust object tracking via ensembling semantic‐aware network and redetection
IET Computer Vision (CVI2), Volume 18, Issue 1February 2024, Pages 46–59https://doi.org/10.1049/cvi2.12219AbstractMost Siamese‐based trackers use classification and regression to determine the target bounding box, which can be formulated as a linear matching process of the template and search region. However, this only takes into account the similarity of ...
We innovatively propose object tracking using semantic‐aware ensemble learning for Siamese networks. We propose for the first time a semantic tag redetection method to rescore the tracker bounding boxes and replace the inaccurate bounding boxes. image ...
- research-articleMay 2023
SiamCCF: Siamese visual tracking via cross‐layer calibration fusion
IET Computer Vision (CVI2), Volume 17, Issue 8December 2023, Pages 869–882https://doi.org/10.1049/cvi2.12201AbstractSiamese networks have attracted wide attention in visual tracking due to their competitive accuracy and speed. However, the existing Siamese trackers usually leverage a fixed linear aggregation of feature maps, which does not effectively fuse the ...
This study proposes a novel Siamese visual tracking method via cross‐layer calibration fusion, termed SiamCCF. We first employ an attention‐based feature fusion module (FFM) by using local attention and non‐local attention to fuse the features from the ...
- research-articleApril 2023
Translation and Scale Invariance for Event-Based Object tracking
NICE '23: Proceedings of the 2023 Annual Neuro-Inspired Computational Elements ConferenceApril 2023, Pages 79–85https://doi.org/10.1145/3584954.3584996Without temporal averaging, such as rate codes, it remains challenging to train spiking neural networks for temporal regression tasks. In this work, we present a novel method to accurately predict spatial coordinates from event data with a fully spiking ...
- research-articleMarch 2023
Online multiple object tracking with enhanced Re‐identification
IET Computer Vision (CVI2), Volume 17, Issue 6September 2023, Pages 676–686https://doi.org/10.1049/cvi2.12191AbstractIn existing online multiple object tracking algorithms, schemes that combine object detection and re‐identification (ReID) tasks in a single model for simultaneous learning have drawn great attention due to their balanced speed and accuracy. ...
We propose a task‐related attention network to reduce the competition between object detection and ReID. we introduce a smooth gradient‐boosting loss function that improves the quality of the extracted ReID features by gradually shifting the focus to the ...
- ArticleMarch 2023
Object Tracking Based on Parzen Particle Filter Using Multiple Cues
Advances in Multimedia Information Processing – PCM 2007Dec 2007, Pages 206–215https://doi.org/10.1007/978-3-540-77255-2_23AbstractParticle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, generic particle filter (GPF) is based on Monte Carlo approach and sampling is a problematic issue. This ...