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Recognizing Hand Gestures Using Motion Trajectories [chapter]

Ming-Hsuan Yang, Narendra Ahuja
2001 Face Detection and Gesture Recognition for Human-Computer Interaction  
First, a multiscale segmentation is performed to generate homogeneous regions in each frame. Regions between consecutive frames are then matched to obtain 2-view correspondences.  ...  W e present a n algorithm for extracting and classifying two-dimensional motion in a n image sequence based o n motion trajectories.  ...  Based on the experiments with 40 ASL gestures, the average recognition rate on the training trajectories is 98.14% and the average recognition rate on the unseen test trajectories is 93.42%.  ... 
doi:10.1007/978-1-4615-1423-7_3 fatcat:lxuvnbnryza4vg4r7pgcyistke

HMM and IOHMM for the Recognition of Mono- and Bi-Manual 3D Hand Gestures

A. Just, O. Bernier, S. Marcel
2004 Procedings of the British Machine Vision Conference 2004  
This work was also funded by the Swiss National Science Foundation through the National Center of Competence in Research (NCCR) on "Interactive Multimodal Information Management (IM2)".  ...  Hence IOHMMs are based on non-homogeneous Markov chains contrary to HMMs.  ...  [4] have proposed Input/Output Hidden Markov Models (IOHMMs). An IOHMM is based on a non-homogeneous Markov chain where emission and transition probabilities depend on the input.  ... 
doi:10.5244/c.18.28 dblp:conf/bmvc/JustBM04 fatcat:magbtc6yszhwdiq7jupkt2x55e

Automatic sign language recognition

George Caridakis, Olga Diamanti, Kostas Karpouzis, Petros Maragos
2008 Proceedings of the 1st ACM international conference on PErvasive Technologies Related to Assistive Environments - PETRA '08  
hand shape contour which is useful for extraction of features related to the handshape and a novel classification scheme incorporating Self-organizing maps, Markov chains and Hidden Markov Models.  ...  Geodesic Active Contours enhanced with skin color and motion information are employed for the hand detection and the extraction of the hand silhouette, while features extracted describe hand trajectory  ...  , Markov chains and Hidden Markov Models.  ... 
doi:10.1145/1389586.1389687 dblp:conf/petra/CaridakisDKM08 fatcat:zswxjv5bavaflerb7pqrtswffm

Transport behavior-mining from smartphones: a review

Valentino Servizi, Francisco C. Pereira, Marie K. Anderson, Otto A. Nielsen
2021 European Transport Research Review  
Smartphone-based travel survey data yields the richest perspective on the study of inter- and intrauser behavioral variations.  ...  on a large scale.  ...  Hidden Markov Models map-match- ing results as benchmark with [78] Validated-by-respondents (69 users only) No GT available.  ... 
doi:10.1186/s12544-021-00516-z fatcat:fdbqa2phszde5afsh6ap5z7tky

Conflation of OpenStreetMap and Mobile Sports Tracking Data for Automatic Bicycle Routing

Cecilia Bergman, Juha Oksanen
2016 Transactions on GIS  
We propose a solution where bikeways are prioritized in map-matching, achieving good performance; the HMM-based method matched correctly on average 94% of the route length.  ...  We apply a Hidden Markov Model (HMM)-based method for matching cycling tracks to a "bicycle network" extracted from crowdsourced OpenStreetMap (OSM) data, and evaluate its effective differences in terms  ...  Cost Functions After being processed via map-matching, trajectories could be represented as sequences of road segments.  ... 
doi:10.1111/tgis.12192 fatcat:guunte36bbflxj2mcgv7nqe5by

Extraction of 2D motion trajectories and its application to hand gesture recognition

Ming-Hsuan Yang, N. Ahuja, M. Tabb
2002 IEEE Transactions on Pattern Analysis and Machine Intelligence  
AbstractÐWe present an algorithm for extracting and classifying two-dimensional motion in an image sequence based on motion trajectories.  ...  First, a multiscale segmentation is performed to generate homogeneous regions in each frame. Regions between consecutive frames are then matched to obtain two-view correspondences.  ...  To classify visual events, a set of Hidden Markov Models (HMMs) are trained with feature vectors extracted from movies of several visual events.  ... 
doi:10.1109/tpami.2002.1023803 fatcat:66yrv7l5mbawjlcnny6vdihreu

Aircraft Trajectory Prediction Made Easy with Predictive Analytics

Samet Ayhan, Hanan Samet
2016 Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '16  
This creates a new form of trajectories which are 4D joint cubes, where each cube is a segment that is associated with not only spatio-temporal attributes but also with weather parameters.  ...  Next, we exploit machine learning techniques to train inference models from historical data and apply a stochastic model, a Hidden Markov Model (HMM), to predict trajectories taking environmental uncertainties  ...  ACKNOWLEDGMENTS The authors would like to thank Milad Gholami and Alexander Wainwright for their assistance with this research.  ... 
doi:10.1145/2939672.2939694 dblp:conf/kdd/AyhanS16 fatcat:nmk7gzdpq5cqphh7ocjkghwime

Fibertract segmentation in position orientation space from high angular resolution diffusion MRI

Patric Hagmann, Lisa Jonasson, Thomas Deffieux, Reto Meuli, Jean-Philippe Thiran, Van J. Wedeen
2006 NeuroImage  
As an example, we choose to adapt to this newly defined high-dimensional non-Euclidean space, called position orientation space, an algorithm based on the hidden Markov random field framework.  ...  Indeed, we show that it is possible to segment efficiently wellknown fibertracts with classical image processing methods provided that the problem is formulated in a five-dimensional space of position  ...  For illustration, we show results obtained by adapting a classical segmentation method based on the hidden random Markov field formalism.  ... 
doi:10.1016/j.neuroimage.2006.02.043 pmid:16815713 fatcat:as5h5etskfdqjbnvv3mxftvppm

Spatio-temporal Based Approaches for Human Action Recognition in Static and Dynamic Background: a Survey

K. Anuradha, N. Sairam
2016 Indian Journal of Science and Technology  
Results were matched with advanced pose estimation algorithms.  ...  To handle occlusion, a model was presented with spatial and temporal consistency. The algorithm was appraised on an outdoor dataset with background clutter and a standard indoor dataset (HumanEva-I).  ...  Earlier methods have used dynamic programming or Hidden Markov Models (HMMs), which has resulted in intrinsic computations.  ... 
doi:10.17485/ijst/2016/v9i5/72065 fatcat:5xxufjhhkrhh7gn26rt6qu3yfa

Survey on Various Gesture Recognition Techniques for Interfacing Machines Based on Ambient Intelligence

C Harshith, Karthik.R. Shastry, Manoj Ravindran, M.V.V.N.S Srikanth, Naveen Lakshmikhanth
2010 International Journal of Computer Science & Engineering Survey  
Besides that, it is not affected by facial expressions.Another important function of the nose is that it is able to indicate the head pose.  ...  Gesture recognition is mainly apprehensive on analyzing the functionality of human wits.  ...  ACKNOWLEDGEMENTS We would like to thank our parents for the blessings that they showered on us and the continuous support we received.  ... 
doi:10.5121/ijcses.2010.1203 fatcat:ae4tw6b5urgi7pnuccw35tavqe

Maximizing height, distance or rotation from real-time analysis visualisation of take-off angles and speed

Richard Green
2006 Journal of Sports Science and Medicine  
Key PointsComputer-vision based marker-free tracking.Real-time biomechanical analysis.Improve tracking using a forward smoothing Particle filter.Automatically segment using hierarchical Hidden Markov Models.Recognize  ...  Motion is automatically segmented using hierarchical Hidden Markov Models and 3D tracking is further stabilized by estimating the joint angles for the next frame using a forward smoothing Particle filter  ...  or rotation with consequent dependencies on phase of joint angles and base of support.  ... 
pmid:24357954 pmcid:PMC3861760 fatcat:ntxkyr3pr5cfbivqker4tixiti

A rule-based event detection system for real-life underwater domain

Concetto Spampinato, Emmanuelle Beauxis-Aussalet, Simone Palazzo, Cigdem Beyan, Jacco van Ossenbruggen, Jiyin He, Bas Boom, Xuan Huang
2013 Machine Vision and Applications  
Then each fish trajectory is modeled and classified using hidden Markov models.  ...  They can continuously monitor marine life while having almost no influence on the environment under observation, which is not the case with observations made by divers for instance.  ...  [20] , histograms and hidden Markov models (HMMs) based on objects' features (such as speed, color, size, aspect ratio) are used for trajectory description.  ... 
doi:10.1007/s00138-013-0509-x fatcat:ywpqbfc7brgtzmdwomctqn44hu

A Survey of Traffic Prediction: from Spatio-Temporal Data to Intelligent Transportation

Haitao Yuan, Guoliang Li
2021 Data Science and Engineering  
Second, we focus on four significant data preprocessing techniques: map-matching, data cleaning, data storage and data compression.  ...  With the development of mobile Internet and position technologies, it is reasonable to collect spatio-temporal data and then leverage these data to achieve the goal of intelligent transportation, and here  ...  [104] first divide trajectories into 10-m segments and then leverage CRF (conditional random field) model to map-match segments onto road networks.  ... 
doi:10.1007/s41019-020-00151-z fatcat:nnnnxnpo3bgk3l4hpr7kk2n4xa

A Survey of Localization Methods for Autonomous Vehicles in Highway Scenarios

Johann Laconte, Abderrahim Kasmi, Romuald Aufrère, Maxime Vaidis, Roland Chapuis
2021 Sensors  
For this purpose, the vehicle needs to be able to take into account the information from several sensors and fuse them with data coming from road maps.  ...  In the context of autonomous vehicles on highways, one of the first and most important tasks is to localize the vehicle on the road.  ...  Hidden Markov Model (HMM) Hidden Markov Model (HMM) models for Map-Matching have been the subject of numerous research studies in connection with tracking problems.  ... 
doi:10.3390/s22010247 pmid:35009790 pmcid:PMC8749843 fatcat:aqd7iddh2za4dbmeyeyxl3kyme


2017 International Journal of Recent Trends in Engineering and Research  
Experiments on the benchmark data set and comparisons with the state-of-theart methods validate the advantages of our algorithm.  ...  For each testing spatio-temporal segment, we search for its best match in the training data set, and determine how normal it is using a dynamic threshold.  ...  Normal Trajectory Abnormal Trajectory One common solution to these problems is to define anomalies as events of low probability with respect to a probabilistic model of normal behaviour.  ... 
doi:10.23883/ijrter.conf.20170331.039.35scm fatcat:ngxzajqri5c4nlrxkpsjzrjws4
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