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Visual Tracking with Online Assessment and Improved Sampling Strategy

Meng Ding, Wen-hua Chen, Li Wei, Yun-feng Cao, Zhou-yu Zhang
2020 IEEE Access  
FEATURE REPRESENTATION FOR TRACKING For the past few years, diverse methods of features representation have been proposed for tracking tasks [28] .  ...  Otherwise, this model is not updated, and then the strategy of combining cyclically shifted with random sampling in deep feature space is employed to track the target.  ... 
doi:10.1109/access.2020.2975224 fatcat:jduomp45tjhrzeegou4f5gydue

Fast Compressive Tracking

Kaihua Zhang, Lei Zhang, Ming-Hsuan Yang
2014 IEEE Transactions on Pattern Analysis and Machine Intelligence  
It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur.  ...  The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects.  ...  Zhang are supported in part by the Hong Kong Polytechnic University ICRG Grant (G-YK79). M.-H.  ... 
doi:10.1109/tpami.2014.2315808 pmid:26352631 fatcat:tnwfx2y53ja4rlppnoe2bvlq6y

Marker-Less Motion Capture of Insect Locomotion With Deep Neural Networks Pre-trained on Synthetic Videos

Ilja Arent, Florian P Schmidt, Mario Botsch, Volker Dürr
2021 Frontiers in Behavioral Neuroscience  
On the other hand, we show that sufficient variation of rotation in the training data is essential for performance, and make concise suggestions about how much variation is required.  ...  For that, we use artificially generated video sequences with known combinations of observed, real animal postures and randomized body position, orientation, and size.  ...  ACKNOWLEDGMENTS We thank Oliver Lieske for technical support with the computing cluster of CITEC, and Yannick Günzel for assistance during the acquisition of the experimental videos.  ... 
doi:10.3389/fnbeh.2021.637806 pmid:33967713 pmcid:PMC8100444 fatcat:6abgmswoezcyjj7jufv63ifcpm

PReFerSim: fast simulation of demography and selection under the Poisson Random Field model

Diego Ortega-Del Vecchyo, Clare D. Marsden, Kirk E. Lohmueller
2016 Bioinformatics  
The Poisson Random Field (PRF) model has become an important tool in population genetics to study weakly deleterious genetic variation under complicated demographic scenarios.  ...  Users can track summaries of genetic variation over time and output trajectories of selected alleles.  ...  Acknowledgements We thank Bernard Kim for the preparation of Conflict of Interest: none declared.  ... 
doi:10.1093/bioinformatics/btw478 pmid:27436562 pmcid:PMC5181561 fatcat:khqzlwsg3jcyrkh5ihe6zw3ltq

Dual Deep Network for Visual Tracking

Zhizhen Chi, Hongyang Li, Huchuan Lu, Ming-Hsuan Yang
2017 IEEE Transactions on Image Processing  
In this paper, we propose a dual network to better utilize features among layers for visual tracking.  ...  Thus we exploit the hierarchical features in different layers of a deep model and design a dual structure to obtain better feature representation from various streams, which is rarely investigated in previous  ...  Online Update We update the model features to account for appearance variation, and at the same time maintain the best tracked target features in the last few frames.  ... 
doi:10.1109/tip.2017.2669880 pmid:28212087 fatcat:3d6dcnroobb6peuku776fosmte

Colocalization analyses of genomic elements: approaches, recommendations and challenges

Chakravarthi Kanduri, Christoph Bock, Sveinung Gundersen, Eivind Hovig, Geir Kjetil Sandve, Jonathan Wren
2018 Bioinformatics  
Scientists often use genomic colocalization analysis to interpret such region sets, for example to identify interesting enrichments and to understand the interplay between the underlying biological processes  ...  Results: Here, we describe the different approaches and provide recommendations for performing genomic colocalization analysis, while also discussing common methodological challenges that may influence  ...  Acknowledgements We thank Boris Simovski for critical reading of the manuscript.  ... 
doi:10.1093/bioinformatics/bty835 pmid:30307532 fatcat:fhey2szrrnakzn3kuyrvk4jba4

Traffic Control Recognition with Speed-Profiles: A Deep Learning Approach

Hao Cheng, Stefania Zourlidou, Monika Sester
2020 ISPRS International Journal of Geo-Information  
The results showed that the deep-learning classifier Conditional Variational Autoencoder can predict regulators with 90% accuracy, outperforming a random forest classifier (88% accuracy) that uses the  ...  In this study we propose a crowdsourced method that harnesses the light-weight GPS tracks from commuting vehicles as Volunteered Geographic Information (VGI) for traffic regulator detection.  ...  Different from the sequential features mentioned above, the random forest model uses two types of features summarized from the GPS tracks: physical and statistical features.  ... 
doi:10.3390/ijgi9110652 fatcat:ggjsridb5rez5g5cvr3fwehfdi

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

Qiaoyuan Liu
2017 Journal of Electronic Imaging (JEI)  
2017) Decontaminate feature for tracking : adaptive tracking via evolutionary feature subset. Journal of Electronic Imaging, 26 (6). Abstract.  ...  In this paper, an effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective  ...  Object Function J 1 : Each feasible solution (random binary string) corresponds to a random combination of the feature vectors.  ... 
doi:10.1117/1.jei.26.6.063025 fatcat:au6i4dn5nnaldpvmg5harv2qpy

Tracking deformable parts via dynamic conditional random fields

Suofei Zhang, Xu Cheng, Haiyan Guo, Lin Zhou, Zhenyang Wu
2014 2014 IEEE International Conference on Image Processing (ICIP)  
Despite the success of many advanced tracking methods in this area, tracking targets with drastic variation of appearance such as deformation, view change and partial occlusion in video sequences is still  ...  In this letter, we take these serious tracking problems into account simultaneously, proposing a dynamic graph based model to track object and its deformable parts at multiple resolutions.  ...  Only related HOG features at neighboring levels in pyramid are extracted for tracking.  ... 
doi:10.1109/icip.2014.7025095 dblp:conf/icip/ZhangCGZW14 fatcat:75m7lh4tunanfihrp3ifh2rcsu

Enhancing the estimation of blood pressure using pulse arrival time and two confounding factors

Hyun Jae Baek, Ko Keun Kim, Jung Soo Kim, Boreom Lee, Kwang Suk Park
2009 Physiological Measurement  
With a very limited number of subjects, we build a universal model to estimate SBP. This model is applied to all subjects without calibration, to estimate and track variations in their SBP.  ...  We fuse these features using Random Forest as regression model, and obtain an estimate of SBP every 30 seconds.  ... 
doi:10.1088/0967-3334/31/2/002 pmid:20009186 fatcat:5faat2yesnc5xmjd6snmwvziyu

Robot Vision for Autonomous Object Learning and Tracking [chapter]

Alberto Sanfeliu
2003 Lecture Notes in Computer Science  
We describe the problems that we have found and some solutions that have been applied in two issues: tracking objects and learning and recognition of 3D objects in robotic environments.  ...  In this paper we present a summary of some of the research that we are developing in the Institute of Robotics of the CSIC-UPC, in the field of Learning and Robot Vision for autonomous mobile robots.  ...  In this way, we have a representation model that can be learned directly from the colour images taken into account the potential variations of the perception features.  ... 
doi:10.1007/978-3-540-24586-5_2 fatcat:2do5pmpbazhbph377wjahntkq4

Robust Object Tracking with a Hierarchical Ensemble Framework [article]

Mengmeng Wang, Yong Liu
2016 arXiv   pre-print
A discriminative model which accounts for the matching degree of local patches is adopted via a bottom ensemble layer, and a generative model which exploits holistic templates is used to search for the  ...  In this paper, we propose a robust object tracking algorithm based on a hierarchical ensemble framework which can incorporate information including individual pixel features, local patches and holistic  ...  Online model update mechanism is quite essential for robust visual tracking to deal with appearance variations. Addressing on this problem, Kalal et al.  ... 
arXiv:1509.06925v2 fatcat:6d3kxspavjhcxp2okmxssg2x3y

Object Tracking with Multi-Classifier Fusion Based on Compressive Sensing and Multiple Instance Learning

Si Chen, Xiaoshun Lu, Xiaosen Chen, Min Chen, Jianghu Chen, Dahan Wang, Shunzhi Zhu
2020 Mathematical Problems in Engineering  
In this framework, we integrate the different discriminative classifiers by learning the varied and compressed feature vectors based on different random projection matrices.  ...  Object tracking is a critical research in computer vision and has attracted significant attention over the past few years.  ...  feature model.  ... 
doi:10.1155/2020/1574054 fatcat:qxwp7n4wdfbbrbipmux2t7msf4

Robust identification of email tracking: A machine learning approach

Johannes Haupt, Benedict Bender, Benjamin Fabian, Stefan Lessmann
2018 European Journal of Operational Research  
Third, we test the predictive power of these features in a benchmarking experiment using a selection of state- of-the-art classifiers to clarify the effectiveness of model-based tracking identification  ...  Second, we propose a set of features geared towards the identification of tracking images under real-world conditions.  ...  For all test sets, the random forest model performs best and thus serves as control model for statistical testing.  ... 
doi:10.1016/j.ejor.2018.05.018 fatcat:5g4vic3r45c7rhwwpzbye6kvru

Robust Visual Tracking Using Structurally Random Projection and Weighted Least Squares

Shengping Zhang, Huiyu Zhou, Feng Jiang, Xuelong Li
2015 IEEE transactions on circuits and systems for video technology (Print)  
Robust visual tracking using structurally random projection and weighted least squares.  ...  Random projection matrices (RP) satisfying the JL lemma have been used for visual tracking in the literature. Li et al. [30] used RP to reduce the features' dimensionality in a 1 tracker.  ...  The reason is that the random projection used in our method for feature dimensionality reduction loses partial useful information, especially when the sequence has very low resolution.  ... 
doi:10.1109/tcsvt.2015.2406194 fatcat:dbo2laresrhzbfqva5hmpcrup4
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