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Abeer Abdulaziz AlArfaj and Hanan Ahmed Hosni Mahmoud
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, curren...
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Praveen Mishra,G.S Prajapati
In this paper, we propose a new tracking method that uses Gaussian combination Model (GCM) and PCA-GCM approach for traffic object tracking. The GCM approach consists of three different Gaussian distributions, the average, standard deviation and weight r...
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Priyank Kalgaonkar and Mohamed El-Sharkawy
Accurate perception is crucial for autonomous vehicles (AVs) to navigate safely, especially in adverse weather and lighting conditions where single-sensor networks (e.g., cameras or radar) struggle with reduced maneuverability and unrecognizable targets....
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Hy Nguyen, Srikanth Thudumu, Hung Du, Kon Mouzakis and Rajesh Vasa
Several approaches have applied Deep Reinforcement Learning (DRL) to Unmanned Aerial Vehicles (UAVs) to do autonomous object tracking. These methods, however, are resource intensive and require prior knowledge of the environment, making them difficult to...
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Jose Antonio Carballo, Javier Bonilla, Jesús Fernández-Reche, Bijan Nouri, Antonio Avila-Marin, Yann Fabel and Diego-César Alarcón-Padilla
Due to the need to know the availability of solar resources for the solar renewable technologies in advance, this paper presents a new methodology based on computer vision and the object detection technique that uses convolutional neural networks (Effici...
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Tingbo Xie and Xifan Yao
An approach for object tracking in logistics warehouses based on YOLOv5 and DeepSORT is proposed, which distinguishes humans from goods, and an evaluation system is established for object tracking in logistics warehouse scenarios.
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Zongxiang Liu, Chunmei Zhou and Junwen Luo
The random finite set (RFS) approach for multi-target tracking is widely researched because it has a rigorous theoretical basis. However, many prior parameters such as the clutter density, survival probability and detection probability of the target, pru...
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Wenjun Zhao, Miaolei Deng, Cong Cheng and Dexian Zhang
Object tracking is aimed at tracking a given target that is only specified in the first frame. Due to the rapid movement and the interference of cluttered backgrounds, object tracking is a significant challenging issue in computer vision. This research p...
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Shanshan Luo, Baoqing Li, Xiaobing Yuan and Huawei Liu
The Discriminative Correlation Filter (DCF) has been universally recognized in visual object tracking, thanks to its excellent accuracy and high speed. Nevertheless, these DCF-based trackers perform poorly in long-term tracking. The reasons include the f...
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Oscar E. Perez-Cham, Cesar Puente, Carlos Soubervielle-Montalvo, Gustavo Olague, Carlos A. Aguirre-Salado and Alberto S. Nuñez-Varela
Object tracking refers to the relocation of specific objects in consecutive frames of a video sequence. Presently, this visual task is still considered an open research issue, and the computer science community attempted solutions from the standpoint of ...
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Jungsup Shin, Heegwang Kim, Dohun Kim and Joonki Paik
Object tracking has long been an active research topic in image processing and computer vision fields with various application areas. For practical applications, the object tracking technique should be not only accurate but also fast in a real-time strea...
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Xinxin Zhen, Shumin Fei, Yinmin Wang and Wei Du
Visual object tracking is an important research topic in the field of computer vision. Tracking?learning?detection (TLD) decomposes the tracking problem into three modules?tracking, learning, and detection?which provides effective ideas for solving the t...
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Qingge Ji, Haoqiang Yu and Xiao Wu
Based on tracking-by-detection, we propose a hierarchical-matching-based online and real-time multi-object tracking approach with deep appearance features, which can effectively reduce the false positives (FP) in tracking. For the purpose of increasing t...
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Senquan Yang, Yuan Xie, Pu Li, Haoxiang Wen, Huan Luo and Zhaoshui He
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Senquan Yang, Yuan Xie, Pu Li, Haoxiang Wen, Huan Luo and Zhaoshui He
Color histogram-based trackers have obtained excellent performance against many challenging situations. However, since the appearance of color is sensitive to illumination, they tend to achieve lower accuracy when illumination is severely variant through...
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Jason Rambach, Alain Pagani, Michael Schneider, Oleksandr Artemenko and Didier Stricker
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Domingo Rodriguez, Cesar Aceros, Juan Valera and Edwin Anaya
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Zhiguo Song, Jifeng Sun and Jialin Yu
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Amith. R,V.N. Manjunath Aradhya
Pág. 62 - 75
Detection and tracking of moving objects in video is essential for many computer vision applications and it is considered as a challenging research issue due to dynamic changes in background, illumination, object size and shape. Many traditional algorith...
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Amith. R,V.N. Manjunath Aradhya
Tracking of moving objects in video sequences are essential for many computer vision applications & it is considered as a challenging research issue due to dynamic changes in objects, shape, complex background, illumination changes and occlusion. Many tr...
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