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Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution [article]

Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi Schambra, Carlos Fernandez-Granda
2021 arXiv   pre-print
To address this, we propose a novel approach for high-resolution action identification, inspired by speech-recognition techniques, which is based on a sequence-to-sequence model that directly predicts  ...  This is an important limitation for applications that require the identification of subtle motions at high temporal resolution.  ...  We thank Dawn Nilsen, and OT EdD for expert advice on the testing battery.  ... 
arXiv:2111.02521v1 fatcat:iacxc6xlsrbw3lzmwycdbd5e5y

Representation, Analysis, and Recognition of 3D Humans

Stefano Berretti, Mohamed Daoudi, Pavan Turaga, Anup Basu
2018 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
., across time), with resulting scans obtained at high-or low-resolution.  ...  The latter also accounts for the temporal component in dynamic data (i.e., sequences of 3D scans acquired with 3D cameras).  ...  at high frame rate.  ... 
doi:10.1145/3182179 fatcat:ds55t4md2na2tibtyg4llerf3q

Heuristically optimal path scanning for high-speed multiphoton circuit imaging

Alexander J. Sadovsky, Peter B. Kruskal, Joseph M. Kimmel, Jared Ostmeyer, Florian B. Neubauer, Jason N. MacLean
2011 Journal of Neurophysiology  
sequences of action potential generation in a population of neurons.  ...  The combination of shortest path calculation and minimization of mirror positioning time allows us to optically monitor a population of neurons in a field of view at high rates with single-spike resolution  ...  Vaidya for early assistance and helpful comments. GRANTS DISCLOSURES No conflicts of interest, financial or otherwise, are declared by the author(s).  ... 
doi:10.1152/jn.00334.2011 pmid:21715667 pmcid:PMC3174822 fatcat:w6twpguhi5dsfp5fdt6eor6ir4

Automatic learning of gait signatures for people identification [article]

F.M. Castro and M.J. Marin-Jimenez and N. Guil and N. Perez de la Blanca
2016 arXiv   pre-print
The experimental results indicate that using spatio-temporal cuboids of optical flow as input data for CNN allows to obtain state-of-the-art results on the gait task with an image resolution eight times  ...  While classical methods typically derive gait signatures from sequences of binary silhouettes, in this work we explore the use of convolutional neural networks (CNN) for learning high-level descriptors  ...  For this purpose, the authors reserve the sequences N1 to N4, from the subject test set, to train the model again and the rest of sequences are used for testing and to obtain the accuracy of the model.  ... 
arXiv:1603.01006v2 fatcat:t5t7bxkbyncfjnbjo6tyipwk2y

Deep Recurrent Convolutional Networks for Video-based Person Re-identification: An End-to-End Approach [article]

Lin Wu, Chunhua Shen, Anton van den Hengel
2016 arXiv   pre-print
In this paper, we present an end-to-end approach to simultaneously learn spatio-temporal features and corresponding similarity metric for video-based person re-identification.  ...  Features from all time-steps are then summarized using temporal pooling to produce an overall feature representation for the complete sequence.  ...  In particular, at each time step t, convolutional resolutions at all levels are leveraged and modeled by deep recurrent convolutional network to estimate hidden representation i.e., h Conv 1 h (a ,1 )  ... 
arXiv:1606.01609v2 fatcat:ygz6wzcjwnaftcaz7tmf4wnfgq

Automatic Learning of Gait Signatures for People Identification [chapter]

Francisco Manuel Castro, Manuel J. Marín-Jiménez, Nicolás Guil, Nicolás Pérez de la Blanca
2017 Lecture Notes in Computer Science  
The experimental results indicate that using spatio-temporal cuboids of optical flow as input data for CNN allows to obtain state-of-the-art results on the gait task with an image resolution eight times  ...  While classical methods typically derive gait signatures from sequences of binary silhouettes, in this work we explore the use of convolutional neural networks (CNN) for learning high-level descriptors  ...  For this purpose, the authors reserve the sequences N1 to N4, from the subject test set, to train the model again and the rest of sequences are used for testing and to obtain the accuracy of the model.  ... 
doi:10.1007/978-3-319-59147-6_23 fatcat:3xg7u6rtpnbrblqtbvbl42zqzy

Analyzing Human Movements from Silhouettes Using Manifold Learning

Liang Wang, David Suter
2006 2006 IEEE International Conference on Video and Signal Based Surveillance  
To find more compact representations of high-dimensional silhouette data, we exploit locality preserving projections (LPP) to achieve low-dimensional manifold embedding.  ...  A novel method for learning and recognizing sequential image data is proposed, and promising applications to vision-based human movement analysis are demonstrated.  ...  These sequence images are captured at a rate of 25 fps with the resolution 352×240. The length of each sequence varies with the pace of the walker, but is generally above 2 gait periods.  ... 
doi:10.1109/avss.2006.25 dblp:conf/avss/WangS06 fatcat:3gk3v35btzgqjlbi7vjpzppfzu

Human detection in surveillance videos and its applications - a review

Manoranjan Paul, Shah M E Haque, Subrata Chakraborty
2013 EURASIP Journal on Advances in Signal Processing  
Detecting human beings accurately in a visual surveillance system is crucial for diverse application areas including abnormal event detection, human gait characterization, congestion analysis, person identification  ...  The first step of the detection process is to detect an object which is in motion.  ...  Due to the derivative operation on the temporal axis, the filter shows high responses at regions of motion.  ... 
doi:10.1186/1687-6180-2013-176 fatcat:hucglmedkrffxdvyo4fi7lthqa

A Survey of the Techniques for The Identification and Classification of Human Actions from Visual Data

Shahela Saif, Samabia Tehseen, Sumaira Kausar
2018 Sensors  
Any advancements in this field are tied to advances in the interrelated fields of object recognition, spatio- temporal video analysis and semantic segmentation.  ...  Recognition of human actions form videos has been an active area of research because it has applications in various domains.  ...  The 'context' stream processes a low resolution complete image, and a 'fovea' stream processes a high resolution cropped center of the image.  ... 
doi:10.3390/s18113979 fatcat:cbag7fm5gnetffzdl26se5r2ge

Super-Resolution Perception for Industrial Sensor Data [article]

Jinjin Gu, Haoyu Chen, Guolong Liu, Gaoqi Liang, Xinlei Wang, Junhua Zhao
2021 arXiv   pre-print
Industrial intelligence relies on high-quality industrial sensor data for system control, diagnosis, fault detection, identification, and monitoring.  ...  Advanced generative models are then proposed to solve the SRP problem.  ...  SISR aims at recovering a high-resolution image from a single low-resolution one. Dong et al. (Dong The relationship of temporal dimension and spatial dimension.  ... 
arXiv:1809.06687v2 fatcat:xumawfushjgthcuirkurz5vqwu

Robot Learning from Demonstration Using Predictive Sequence Learning [chapter]

Erik Billing, Thomas Hellstrm, Lars-Erik Janlert
2012 Robotic Systems - Applications, Control and Programming  
Modules at the bottom layer are given the highest resolution while modules higher up in the hierarchy have decreasing temporal resolution.  ...  Long temporal dependencies are modeled by switching between modules, which removes the requirement for each model to capture these dependencies.  ...  This book brings together some of the latest research in robot applications, control, modeling, sensors and algorithms.  ... 
doi:10.5772/26165 fatcat:h5rxub2tb5g7nctxzwvj7jkaly

Bio-Inspired Optic Flow from Event-Based Neuromorphic Sensor Input [chapter]

Stephan Tschechne, Roman Sailer, Heiko Neumann
2014 Lecture Notes in Computer Science  
Computational models of visual processing often use framebased image acquisition techniques to process a temporally changing stimulus.  ...  Our model combines filters with spatio-temporal tunings also found in visual cortex to yield spatiotemporal and direction specificity.  ...  .: High Accuracy Optical Flow Estimation Based on a Theory for Warping. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 25-36.  ... 
doi:10.1007/978-3-319-11656-3_16 fatcat:adym3otnfrhd5ovkm562gmy77m

Guest Editorial Introduction to the Special Section on Intelligent Visual Content Analysis and Understanding

Hongliang Li, Lu Fang, Tianzhu Zhang
2020 IEEE transactions on circuits and systems for video technology (Print)  
To this end, a Nearest Neighbor Network is built in the training stage to model the neighbor relationship through similarity between Low-Resolution (LR) human face image patches and High-Resolution (HR  ...  "Multi-exposure decomposition-fusion model for high dynamic range image saliency detection," by Wang et al., presents a two-stage framework to estimate the saliency map toward high dynamic range (HDR)  ... 
doi:10.1109/tcsvt.2020.3031416 fatcat:gpwbmydqbza5lddatxcfcidwcq

Action Recognition Using Single-Pixel Time-of-Flight Detection

Ikechukwu Ofodile, Ahmed Helmi, Albert Clapés, Egils Avots, Kerttu Maria Peensoo, Sandhra-Mirella Valdma, Andreas Valdmann, Heli Valtna-Lukner, Sergey Omelkov, Sergio Escalera, Cagri Ozcinar, Gholamreza Anbarjafari
2019 Entropy  
Such data trace to record one action contains a sequence of one-dimensional arrays of voltage values acquired by a single-pixel detector at 1 GHz repetition rate.  ...  In this paper, we propose a concept for detecting actions while preserving the test subject's privacy.  ...  Acknowledgments: We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp and V GPUs used for this research.  ... 
doi:10.3390/e21040414 pmid:33267128 fatcat:xhujztfdj5b4revpbyemwuyxkq

Multimodal feature fusion for CNN-based gait recognition: an empirical comparison [article]

Francisco Manuel Castro, Manuel Jesús Marín-Jiménez, Nicolás Guil, Nicolás Pérez de la Blanca
2020 arXiv   pre-print
People identification in video based on the way they walk (i.e. gait) is a relevant task in computer vision using a non-invasive approach.  ...  Standard and current approaches typically derive gait signatures from sequences of binary energy maps of subjects extracted from images, but this process introduces a large amount of non-stationary noise  ...  We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan X Pascal GPU used for this research.  ... 
arXiv:1806.07753v2 fatcat:ivofhg5ryfbepk2fv2fkx6z3va
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