On the Combination of IMU and Optical Flow for Action Recognition

Different Action recognition methods use Inertial Measurement Unit (IMU) and optical flow independently. This research aims to explore the usefulness of combining IMU and Optical flow for action recognition. We are investigating the effectiveness of using statistical features to build an expandable feature vector space.

[1]  Jan Kautz,et al.  PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[2]  Wei Zhang,et al.  Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[3]  Nicu Sebe,et al.  Video classification with Densely extracted HOG/HOF/MBH features: an evaluation of the accuracy/computational efficiency trade-off , 2015, International Journal of Multimedia Information Retrieval.

[4]  Nassir Navab,et al.  Human Motion Analysis with Deep Metric Learning , 2018, ECCV.

[5]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[6]  Marek B. Zaremba,et al.  Wearable Sensor Data Classification for Human Activity Recognition Based on an Iterative Learning Framework † , 2017, Sensors.

[7]  Thomas Brox,et al.  FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[8]  Rogelio Lozano,et al.  FUSION OF OPTICAL FLOW AND INERTIAL SENSORS FOR FOUR-ROTOR ROTORCRAFT STABILIZATION , 2007 .

[9]  Dirk Krechel,et al.  Human Action Recognition Using Optical Flow and Convolutional Neural Networks , 2017, 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA).

[10]  Thomas Brox,et al.  FlowNet: Learning Optical Flow with Convolutional Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[11]  Ferda Nur Alpaslan,et al.  Video Action Recognition Using an Optical Flow Based Representation , 2022 .

[12]  Michael J. Black,et al.  On the Integration of Optical Flow and Action Recognition , 2017, GCPR.

[13]  Jean-Christophe Nebel,et al.  Recognition of Activities of Daily Living with Egocentric Vision: A Review , 2016, Sensors.

[14]  Patrick Bouthemy,et al.  Optical flow modeling and computation: A survey , 2015, Comput. Vis. Image Underst..

[15]  Cordelia Schmid,et al.  Human Detection Using Oriented Histograms of Flow and Appearance , 2006, ECCV.

[16]  Faicel Chamroukhi,et al.  Physical Human Activity Recognition Using Wearable Sensors , 2015, Sensors.

[17]  Stephen J. McKenna,et al.  Computer Vision and Image Understanding Recognising Complex Activities with Histograms of Relative Tracklets , 2022 .

[18]  Leonidas J. Guibas,et al.  A metric for distributions with applications to image databases , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[19]  Hannes Sommer,et al.  Fusion of optical flow and inertial measurements for robust egomotion estimation , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[20]  Jitendra Malik,et al.  Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  Anne S. Wannenwetsch,et al.  ProbFlow: Joint Optical Flow and Uncertainty Estimation , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[22]  Chalavadi Krishna Mohan,et al.  Human action recognition in RGB-D videos using motion sequence information and deep learning , 2017, Pattern Recognit..

[23]  S. Santhosh Kumar,et al.  Human activity recognition using optical flow based feature set , 2016, 2016 IEEE International Carnahan Conference on Security Technology (ICCST).

[24]  Jessica K. Hodgins,et al.  Guide to the Carnegie Mellon University Multimodal Activity (CMU-MMAC) Database , 2008 .