Results 11 to 20 of about 68,167 (308)
Variational Bayes for Robust Radar Single Object Tracking [PDF]
2022 IEEE Workshop on Signal Processing Systems (SiPS), 2022 We address object tracking by radar and the robustness of the current state-of-the-art methods to process outliers. The standard tracking algorithms extract detections from radar image space to use it in the filtering stage. Filtering is performed by a Kalman filter, which assumes Gaussian distributed noise.
Alp Sari +3 more
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Sparsity based Single Object Tracking [PDF]
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2013 Object tracking has importance in various video processing applications like video surveillance, perceptual user interface driver assistance, tracking etc. This paper deals with a new tracking technique that combines the dictionary based background subtraction along with sparsity based tracking.
Glincy Abraham +2 more
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Beyond traditional single object tracking [PDF]
Single object tracking is a crucial yet challenging task in computer vision. In this task, a model is given the appearance of an arbitrary object in a sequence of frames. The model is required to track the object in all sequence frames. Traditionally, discriminative correlation filters and Siamese convolutional networks have dominated the field but ...
Abdelaziz, Omar
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Single Object Tracking Research: A Survey
CoRR, 2022 Visual object tracking is an important task in computer vision, which has many real-world applications, e.g., video surveillance, visual navigation. Visual object tracking also has many challenges, e.g., object occlusion and deformation. To solve above problems and track the target accurately and efficiently, many tracking algorithms have emerged in ...
Ruize Han +3 more
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On-line fusion of trackers for single-object tracking [PDF]
Pattern Recognition, 2018 Abstract Visual object tracking is a fundamental function of computer vision that has been the object of numerous studies. The diversity of the proposed approaches leads to the idea of trying to fuse them and take advantage of their individual strengths while controlling the noise they may introduce in some circumstances.
Leang, Isabelle +3 more
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Deep Feature Based Siamese Network for Visual Object Tracking
Energies, 2022 One of the most important and challenging research subjects in computer vision is visual object tracking. The information obtained from the first frame consists of limited and insufficient information to represent an object.
Su-Chang Lim, Jun-Ho Huh, Jong-Chan Kim
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Enhanced Multiple-Object Tracking Using Delay Processing and Binary-Channel Verification
Applied Sciences, 2019 Tracking objects over time, i.e., identity (ID) consistency, is important when dealing with multiple object tracking (MOT). Especially in complex scenes with occlusion and interaction of objects this is challenging.
Muyu Li +5 more
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A TOOL TO ENHANCE THE CAPACITY FOR DEEP LEARNING BASED OBJECT DETECTION AND TRACKING WITH UAV DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Currently, deployment of UAV has transformed from crucial to day-to-day scenarios for various purposes such as wastage collection, live entertainment, product delivery, town mapping, etc. Object tracking based UAV applications such as traffic monitoring,
A. A. Micheal +3 more
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SMOT: Single-Shot Multi Object Tracking
CoRR, 2020 We present single-shot multi-object tracker (SMOT), a new tracking framework that converts any single-shot detector (SSD) model into an online multiple object tracker, which emphasizes simultaneously detecting and tracking of the object paths. Contrary to the existing tracking by detection approaches which suffer from errors made by the object ...
Wei Li +4 more
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On-line learning of shape information for object segmentation and tracking [PDF]
, 2009 We present segmentation and tracking of deformable objects using non-linear on-line learning of high-level shape information in the form of a level set function.
Chiverton, John +7 more
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