187,842 Hits in 4.5 sec

Biometric Person Authentication Method Using Camera-Based Online Signature Acquisition

Daigo Muramatsu, Kumiko Yasuda, Takashi Matsumoto
2009 2009 10th International Conference on Document Analysis and Recognition  
A camera-based online signature verification system is proposed in this paper. One web camera is used for data acquisition, and a sequential Monte Carlo method is used for tracking a pen tip.  ...  Several distances are computed from an online signature, and a fusion model trained by using Ad-aBoost combines the distances and computes a final score.  ...  Acknowledgement This work was supported by the New-Generation Information Security Technologies R&D project (Ministry of Economy, Trade and Industry of Japan).  ... 
doi:10.1109/icdar.2009.112 dblp:conf/icdar/MuramatsuYM09 fatcat:4z3sn3tm3ffurkptll552uvz6a

The Tussle around Online Privacy

Vijay Erramilli
2012 IEEE Internet Computing  
However, for most of these startups, the business model isn't clear; the services are being offered for free, and, at some point, these firms must start generating revenue with the only asset they will  ...  Chrome, for instance, doesn't support the "do-not-track" header.  ... 
doi:10.1109/mic.2012.92 fatcat:kwytluzl4naahiibwtemwfm7wu

Implementation of Dual Decision Support System for Students and Teachers using Data Analytics in Online Exam

Kalyani V. Deshmukh
2021 International Journal for Research in Applied Science and Engineering Technology  
In this system, we proposed a personal questions ordering module for students depending upon their historical question solving patterns.  ...  We proposed a decision support system in online learning system for tutors/teachers which will help them to improve their learning quality.  ...  On the other hand, question solving behavior will be tracked in database at the time of online exam to generate live dashboards and calculate student's performance.  ... 
doi:10.22214/ijraset.2021.36677 fatcat:3h6e6vbhnbd3nexfbxaarqit4i

An Effective and Efficient Method for Detecting Hands in Egocentric Videos for Rehabilitation Applications [article]

Ryan J. Visée, Jirapat Likitlersuang, José Zariffa
2019 arXiv   pre-print
We propose an accurate and efficient hand detection method that uses a simple combination of existing detection and tracking algorithms.  ...  Methods: Detection, tracking, and combination methods were evaluated on a new hand detection dataset, consisting of 167,622 frames of egocentric videos collected on 17 individuals with SCI performing activities  ...  For hand tracking, we implemented 4 online tracking algorithms due to their efficiency on CPU processors; Online Boosting (OLB), Multiple Instance Learning (MIL), KCF, and MF [34] , [26] - [28] .  ... 
arXiv:1908.10406v1 fatcat:qw337xl6bffojal372iyb6vgv4

Particle Filter Based Monocular Human Tracking with a 3D Cardbox Model and a Novel Deterministic Resampling Strategy [article]

Ziyuan Liu, Dongheui Lee, Wolfgang Sepp
2020 arXiv   pre-print
Moreover, a new 3D articulated human upper body model with the name 3D cardbox model is created and is proven to work successfully for motion tracking.  ...  In this paper, a motion capturing algorithm is proposed for upper body motion tracking.  ...  Offline Model Initialization Before the human model is used for online motion tracking, it must be initialized, which means the body size parameters of the human model are tuned for the observed person  ... 
arXiv:2002.09554v1 fatcat:mkgkj5klcfafrc64jznxnn26mm


2004 International Journal of Image and Graphics  
Today's performance of off-the-shelf computer hardware enables marker-free non-intrusive optical tracking of the human body.  ...  A person is recorded by multiple synchronized cameras, and a multilayer hierarchical kinematic skeleton is fitted to each frame in a two-stage process.  ...  In the online component, the visual hull is reconstructed from four camera views, and the 3D positions of the head, hands and feet are automatically identified and tracked.  ... 
doi:10.1142/s0219467804001543 fatcat:bmymrrmg7ffxrhprl4kxhgseva

Fits Like a Glove: Rapid and Reliable Hand Shape Personalization

David Joseph Tan, Thomas Cashman, Jonathan Taylor, Andrew Fitzgibbon, Daniel Tarlow, Sameh Khamis, Shahram Izadi, Jamie Shotton
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Experimental results quantitatively demonstrate for the first time that detailed personalized models improve the accuracy of hand tracking and achieve competitive results in both tracking and model registration  ...  We present a fast, practical method for personalizing a hand shape basis to an individual user's detailed hand shape using only a small set of depth images.  ...  Further, they did not investigate whether the use of a personalized model was important for the accuracy of online hand tracking systems.  ... 
doi:10.1109/cvpr.2016.605 dblp:conf/cvpr/TanCTFTKIS16 fatcat:erfgrculhzcepojvnhy43n52j4

Applying a micro-UAV for searching an indoor target person using laser ranging and monocular vision

Bo CAI, YuTing MA, TianYu GAO, ChengZhe HAN, Rui WENG, LiXian ZHANG
2020 Scientia Sinica Technologica  
Figure 4 (Figure 5 (Figure 6 456 Color online) Camera modeling and safe flight area.图 5 (网络版彩图)深度阈值图的生成 Color online) Generation of depth threshold graph.  ...  Figure 14 (Figure 16 (Figure 15 ( 141615 Color online) Variation curve of accuracy rate after training with 500000 pictures.图 16 (网络版彩图)多种算法的目标追踪效果对比测试 Color online) Comparison test of target tracking  ...  For the purpose of detecting and tracking the target person during the search process, the YOLOv3 object detection algorithm is used to detect the human body, face, and hands.  ... 
doi:10.1360/sst-2020-0130 fatcat:l6qfrflddrawddm6oqyq267rnm

Leveraging Long-Term Predictions and Online Learning in Agent-Based Multiple Person Tracking

Wenxi Liu, Antoni B. Chan, Rynson W. H. Lau, Dinesh Manocha
2015 IEEE transactions on circuits and systems for video technology (Print)  
Experimental results show that our tracking algorithm is suitable for predicting pedestrians' behaviors online without needing scene priors or hand-annotated goal information, and improves tracking in  ...  We present a multiple-person tracking algorithm, based on combining particle filters and RVO, an agent-based crowd model that infers collision-free velocities so as to predict pedestrian's motion.  ...  RVO. • We demonstrate that our RVO-based online tracking algorithm improves tracking in low frame rate crowd video, compared to other motion models, while not requiring scene priors or hand-annotated  ... 
doi:10.1109/tcsvt.2014.2344511 fatcat:vjbrjjhcgzb3nalvqdzgxfuqea

Person re-identification in multi-camera networks

Kai Jungling, Christoph Bodensteiner, Michael Arens
2011 CVPR 2011 WORKSHOPS  
In this paper, we present an approach for person reidentification in multi-camera networks. This approach employs the Implicit Shape Model and SIFT features for person re-identification.  ...  One important property of the reidentification approach is that it is closely coupled to a person detection and tracking and uses SIFT feature models which are built during the tracking.  ...  For that we outlined an integrated approach for person tracking and reidentification which is based on the Implicit Shape Model and SIFT features only and thus generically applicable.  ... 
doi:10.1109/cvprw.2011.5981771 dblp:conf/cvpr/JunglingBA11 fatcat:zzbguxztrbduzpymesidgbnpbq

Online Full Body Human Motion Tracking Based on Dense Volumetric 3D Reconstructions from Multi Camera Setups [chapter]

Tobias Feldmann, Ioannis Mihailidis, Sebastian Schulz, Dietrich Paulus, Annika Wörner
2010 Lecture Notes in Computer Science  
The image data of calibrated video cameras is used to generate dense volumentric reconstructions of a person within the capure volume.  ...  We present an approach for video based human motion capture using a static multi camera setup.  ...  model based pose tracking of the observed person.  ... 
doi:10.1007/978-3-642-16111-7_8 fatcat:voavealx2jc3vjiytb4pq72eq4

Online Appearance-Motion Coupling for Multi-Person Tracking in Videos

Bonan Cuan, Khalid Idrissi, Christophe Garcia
2019 International Journal of Modeling and Optimization  
s model multi-person tracking is an offline lifted multi-cut problem (LMP).  ...  As a multi-object tracking (MOT) problem, it has several intrinsic challenges compared to generic object tracking tasks.  ... 
doi:10.7763/ijmo.2019.v9.687 fatcat:iiwgletz6fdvblqz34p2qk4amq

Personalized Rehabilitation Robotics based on Online Learning Control [article]

Samuel Tesfazgi, Armin Lederer, Johannes F. Kunz, Alejandro J. Ordóñez-Conejo, Sandra Hirche
2021 arXiv   pre-print
Generally, the required personalization is achieved through manual tuning by clinicians, which is cumbersome and error-prone.  ...  In this work we propose a novel online learning control architecture, which is able to personalize the control force at run time to each individual user.  ...  Online Data Generation and Model Inference In order to account for the individual human-induced dynamics in the controller, it is necessary to infer a model online from data.  ... 
arXiv:2110.00481v1 fatcat:2mnci4bsujc4zhs4hfm4vactyu

Temporal dynamic appearance modeling for online multi-person tracking

Min Yang, Yunde Jia
2016 Computer Vision and Image Understanding  
Moreover, the appearance model is learned incrementally by alternatively evaluating newly-observed appearances and adjusting the model parameters to be suitable for online tracking.  ...  Reliable tracking of multiple persons in complex scenes is achieved by incorporating the learned model into an online tracking-by-detection framework.  ...  Conclusions In this paper, we have proposed a novel appearance modeling algorithm for online multi-person tracking.  ... 
doi:10.1016/j.cviu.2016.05.003 fatcat:bphga2pbkfgizk7otouz7lma2m

Combining Visual Tracking and Person Detection for Long Term Tracking on a UAV [chapter]

Gustav Häger, Goutam Bhat, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg, Piotr Rudl, Patrick Doherty
2016 Lecture Notes in Computer Science  
Methods based on online learning provide high accuracy, but are prone to model drift. The model drift occurs when the tracker fails to correctly estimate the tracked objects position.  ...  Methods based on a detector on the other hand typically have good long-term robustness, but reduced accuracy compared to online methods.  ...  Detection based trackers on the other hand use a detector for the object or class to track, this detector is applied on each new frame.  ... 
doi:10.1007/978-3-319-50835-1_50 fatcat:sojzox527bar7hfh6hdl7td37u
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