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Particle Filter Based Probabilistic Forced Alignment for Continuous Gesture Recognition

Necati Cihan Camgoz, Simon Hadfield, Richard Bowden
2017 2017 IEEE International Conference on Computer Vision Workshops (ICCVW)  
In this paper, we propose a novel particle filter based probabilistic forced alignment approach for training spatiotemporal deep neural networks using weak border level annotations.  ...  We evaluate the performance on the popular ChaLearn 2016 Continuous Gesture Recognition (ConGD) dataset.  ...  We would also like to thank NVIDIA Corporation for their GPU grant.  ... 
doi:10.1109/iccvw.2017.364 dblp:conf/iccvw/CamgozHB17 fatcat:rvxu7i3xinekfayrigpqoxagya

Adaptive Gesture Recognition with Variation Estimation for Interactive Systems

Baptiste Caramiaux, Nicola Montecchio, Atau Tanaka, Frédéric Bevilacqua
2014 ACM transactions on interactive intelligent systems (TiiS)  
The method continuously updates, during execution of the gesture, the estimated parameters and recognition results which offers key advantages for continuous human-machine interaction.  ...  We describe a template-based recognition method that simultaneously aligns the input gesture to the templates using a Sequential Montecarlo inference technique.  ...  The extension of the tracking algorithm for the recognition task is detailed in Section 4.6. The inference is based on particle filtering with a resampling process.  ... 
doi:10.1145/2643204 fatcat:ggfjzmp2kjeupgje226t7dmcvi

RGBD Video Based Human Hand Trajectory Tracking and Gesture Recognition System

Weihua Liu, Yangyu Fan, Zuhe Li, Zhong Zhang
2015 Mathematical Problems in Engineering  
The task of human hand trajectory tracking and gesture trajectory recognition based on synchronized color and depth video is considered.  ...  Moreover, the shape-order context leads to a robust score for gesture invariant.  ...  Meanwhile, it is treated as the input of recognition phase as well for gesture classification. Probabilistic Tracking Overview Particle Filter.  ... 
doi:10.1155/2015/863732 fatcat:jaj44xzpb5attingozkzv4aucq

Audiovisual Information Fusion in Human–Computer Interfaces and Intelligent Environments: A Survey

Shankar T. Shivappa, Mohan Manubhai Trivedi, Bhaskar D. Rao
2010 Proceedings of the IEEE  
In this paper we describe the fusion strategies and the corresponding models used in audiovisual tasks such as speech recognition, tracking, biometrics, affective state recognition and meeting scene analysis  ...  The fusion strategy used tends to depend mainly on the model, probabilistic or otherwise, used in the particular task to process sensory information to obtain higher level semantic information.  ...  We sincerely thank the reviewers for their valuable advise which has helped us enhance the content as well as the presentation of the paper.  ... 
doi:10.1109/jproc.2010.2057231 fatcat:lfzgfmn2hjdq7h6o5txva3oapq

Machine Learning Of Musical Gestures

Baptiste Caramiaux, Atau Tanaka
2013 Zenodo  
We then present a review of the literature in current NIMEresearch that uses ML in musical gesture analysis and gestural sound control.We describe the ways in which machine learning is useful for creatingexpressive  ...  musical interaction, and in turn why live music performance presentsa pertinent and challenging use case for machine learning.  ...  Other methods such as linear SVM, HMM, and Particle Filtering each offer specific advantages like continuous classification and adaptation to variation.  ... 
doi:10.5281/zenodo.1178489 fatcat:3axprilmlvcdzlbrxcmr7zwdti

Vision-Based Hand Gesture Recognition for Human-Computer Interaction [chapter]

Xenophon Zabulis, Haris Baltzakis, Antonis Argyros
2009 Human Factors and Ergonomics  
In [KM03] , continuous states are utilized for gesture recognition in a multi-view context.  ...  Particle filtering Particle filters have been utilized to track the position of hands and the configuration of fingers in dense visual clutter.  ... 
doi:10.1201/9781420064995-c34 fatcat:ethpj6kys5dpdjihszbkjgqewa

Intelligent visual surveillance — A survey

In Su Kim, Hong Seok Choi, Kwang Moo Yi, Jin Young Choi, Seong G. Kong
2010 International Journal of Control, Automation and Systems  
The second part reviews widearea surveillance techniques based on the fusion of multiple visual sensors, camera calibration and cooperative camera systems.  ...  Visual surveillance often employs gross and intermediate level recognition, and detailed level recognition mainly aims for developing the gesture based human-computer interfaces (HCI) [56] .  ...  Isard [50] presented a contour tracking method based on the particle filter, as known as the Condensation algorithm.  ... 
doi:10.1007/s12555-010-0501-4 fatcat:pdv6jpfqfnfiraqe4ngxzvywvu

Vision based hand gesture recognition for human computer interaction: a survey

Siddharth S. Rautaray, Anupam Agrawal
2012 Artificial Intelligence Review  
The use of hand gestures as a natural interface serves as a motivating force for research in gesture taxonomies, its representations and recognition techniques, software platforms and frameworks which  ...  It focuses on the three main phases of hand gesture recognition i.e. detection, tracking and recognition.  ...  Particle filtering Particle filters have been utilized to track the position of hands and the configuration of fingers in dense visual clutter.  ... 
doi:10.1007/s10462-012-9356-9 fatcat:qtmmnc5bdfatnjyryw724nvy2i

Learning Deep and Wide: A Spectral Method for Learning Deep Networks

Ling Shao, Di Wu, Xuelong Li
2014 IEEE Transactions on Neural Networks and Learning Systems  
Various applications spawned after the inception of this consumer priced 3D camera: scene flow estimation using a particle filter was formulated in [51] ; human activity detection from RGBD images based  ...  The outputs of the neural net are the hidden states learned by force alignment during the supervised training process.  ...  from RGBD Images The Matlab code for generating "One Shot Learning Gesture Recognition from RGBD Images" for section 2.3 can be found at: https://github.com/stevenwudi/Kaggle_one_shot_learning Matlab  ... 
doi:10.1109/tnnls.2014.2308519 pmid:25420251 fatcat:4mnl6tv2xnf3jpzwhp76cvl4ti

Single camera pose estimation using Bayesian filtering and Kinect motion priors [article]

Michael Burke, Joan Lasenby
2014 arXiv   pre-print
object recognition strategies.  ...  We combine this prior information with a random walk transition model to obtain an upper body model, suitable for use within a recursive Bayesian filtering framework.  ...  Background and related work Effective human pose estimation is required for successful vision-based gesture recognition systems to be deployed.  ... 
arXiv:1405.5047v2 fatcat:u4zkpuomtzeoddel4bmihrcdg4

A Study on Visual Focus of Attention Recognition from Head Pose in a Meeting Room [chapter]

Sileye O. Ba, Jean-Marc Odobez
2006 Lecture Notes in Computer Science  
This paper presents a study on the recognition of the visual focus of attention (VFOA) of meeting participants based on their head pose.  ...  The results clearly show that in complex but realistic situations, it is quite optimistic to believe that the recognition of the VFOA can solely be based on the head pose, as some previous studies had  ...  For both person right and left, the GMM modeling is achieving better performances in term of frame based recognition rate and event based recall while the HMM is giving better event based precision.  ... 
doi:10.1007/11965152_7 fatcat:z3lq3itmonfy7gxbgmzxggga4a

Cooperative Object Segmentation and Behavior Inference in Image Sequences

Laura Gui, Jean-Philippe Thiran, Nikos Paragios
2008 International Journal of Computer Vision  
We demonstrate the effectiveness of our framework via particular implementations that we have employed in the resolution of two hand gesture recognition applications.  ...  In particular, the behavior inference process offers dynamic probabilistic priors to guide segmentation.  ...  The coherence between frames has been exploited by approaches based on Kalman filtering (Terzopoulos and Szeliski 1992) , particle filtering (Rathi et al. 2007) , and autoregressive models (Cremers  ... 
doi:10.1007/s11263-008-0146-4 fatcat:24hp2k6jjbdipmjeiv722ca3vi

A review of motion analysis methods for human Nonverbal Communication Computing

Dimitris Metaxas, Shaoting Zhang
2013 Image and Vision Computing  
They include face tracking, expression recognition, body reconstruction, and group activity analysis.  ...  In general, nonverbal communication research offers high-level principles that might explain how people organize, display, adapt and understand such behaviors for communicative purposes and social goals  ...  Acknowledgments The authors would like to thank all the reviewers for their constructive suggestions.  ... 
doi:10.1016/j.imavis.2013.03.005 fatcat:ylxt5bph2jfgrfd5a4c22qn66u

Video-Based Human Behavior Understanding: A Survey

Paulo Vinicius Koerich Borges, Nicola Conci, Andrea Cavallaro
2013 IEEE transactions on circuits and systems for video technology (Print)  
The advantages and the drawbacks of the methods are critically discussed, providing a comprehensive coverage of key aspects of video-based human behavior understanding, available datasets for experimentation  ...  this paper we organize and survey the corresponding literature, define unambiguously key terms and discuss links among fundamental building blocks ranging from human detection to action and interaction recognition  ...  [156] use grid of particles over the image that are moved by the forces created by the spacetime optical flow as they were individuals.  ... 
doi:10.1109/tcsvt.2013.2270402 fatcat:ilpqptjrhfacjasyyw6wfug7ia

Tracking identities and attention in smart environments - contributions and progress in the CHIL project

Rainer Stiefelhagen, Keni Bernardin, Hazim K. Ekenel, Michael Voit
2008 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition  
This includes, for example, the number of people, their identities, locations, postures, body and head orientations, among others.  ...  These were notably particle filter based trackers [6, 8, 39] , as these allow for a flexible integration of features across sensors and modalities.  ...  For accounting uncertainty and ambiguity, a particle filter allows to propagate numerous hypotheses (particles), and low-dimensional shape and appearance models (color histgrams) for different body parts  ... 
doi:10.1109/afgr.2008.4813322 dblp:conf/fgr/StiefelhagenBEV08 fatcat:r5c2i2vyrngwdmx4wet6pmmhsa
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