1 Activity Discovery and Activity Recognition: A New Partnership Diane Cook, Fellow, IEEE, Narayanan Krishnan, Member, IEEE, and Parisa Rashidi, Member, IEEE

Source URL: eecs.wsu.edu

Activity Recognition on Streaming Sensor Data Narayanan C Krishnan, Diane J Cook School of Electrical Engineering and Computer Science Washington State University Pullman, WA, USA

Source URL: eecs.wsu.edu

Transfer Learning for Activity Recognition: A Survey Diane Cook, Kyle D. Feuz, and Narayanan C. Krishnan Abstract Many intelligent systems that focus on the needs of a human require information about the activities being

Source URL: eecs.wsu.edu

Physical Activity Recognition from Body-worn Sensors: A Comparison of Free-living and Controlled Data Collection

Source URL: eceweb.ucsd.edu

Enhancing Accelerometer-based Activity Recognition with Capacitive Proximity Sensing Tobias Grosse-Puppendahl1 , Eugen Berlin2 , and Marko Borazio2 2

Source URL: www.grosse-puppendahl.com

Certificate of Participation This certificate is presented to _________________________________ (name) in recognition of participation in ________________________________ (activity, location) as part of the international

Source URL: webwewant.org

IEEE Conference on Computer Vision and Pattern Recognition Workshops: Human Activity Understanding from 3D Data, to appearJoint Angles Similarities and HOG2 for Action Recognition Eshed Ohn-Bar and Mohan M. Trived

Source URL: cvrr.ucsd.edu

Activity Recognition using Dynamic Subspace Angles Robust Systems Lab

Source URL: www.northeastern.edu

Collective Activity Detection using Hinge-loss Markov Random Fields Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry Davis University of Maryland College Park, MD 20742 {blondon,sameh,bach,bert,g

Source URL: psl.umiacs.umd.edu

• Artificial intelligence
• Probability
• Statistics
• Bayesian statistics
• Markov networks
• Graphical models
• Markov random field
• Probability theory
• Image segmentation
• Probabilistic soft logic
• Activity recognition
• Support vector machine

Surveillance Event Detection Mert Dikmen, Huazhong Ning, Dennis J. Lin, Liangliang Cao, Vuong Le, Shen-Fu Tsai, Kai-Hsiang Lin, Zhen Li, Jianchao Yang, Thomas S. Huang Department of Electrical and Computer Engineering Un

Source URL: www.ifp.illinois.edu

• Artificial intelligence
• Computer vision
• Image processing
• Feature detection
• Statistical theory
• Conference on Computer Vision and Pattern Recognition
• Conditional random field
• Optical flow
• Edge detection
• Thomas Huang
• Activity recognition
• Loss function