Back to Search
Start Over
Making the Invisible Visible: Action Recognition Through Walls and Occlusions
- Source :
- ICCV, arXiv
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- Understanding people's actions and interactions typically depends on seeing them. Automating the process of action recognition from visual data has been the topic of much research in the computer vision community. But what if it is too dark, or if the person is occluded or behind a wall? In this paper, we introduce a neural network model that can detect human actions through walls and occlusions, and in poor lighting conditions. Our model takes radio frequency (RF) signals as input, generates 3D human skeletons as an intermediate representation, and recognizes actions and interactions of multiple people over time. By translating the input to an intermediate skeleton-based representation, our model can learn from both vision-based and RF-based datasets, and allow the two tasks to help each other. We show that our model achieves comparable accuracy to vision-based action recognition systems in visible scenarios, yet continues to work accurately when people are not visible, hence addressing scenarios that are beyond the limit of today's vision-based action recognition.<br />ICCV 2019. The first two authors contributed equally to this paper
- Subjects :
- FOS: Computer and information sciences
Computer Science - Machine Learning
Computer science
Process (engineering)
Computer Vision and Pattern Recognition (cs.CV)
Feature extraction
Computer Science - Computer Vision and Pattern Recognition
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
02 engineering and technology
010501 environmental sciences
01 natural sciences
Machine Learning (cs.LG)
FOS: Electrical engineering, electronic engineering, information engineering
0202 electrical engineering, electronic engineering, information engineering
Computer vision
0105 earth and related environmental sciences
Artificial neural network
business.industry
Image and Video Processing (eess.IV)
Representation (systemics)
Electrical Engineering and Systems Science - Image and Video Processing
Visualization
Action recognition
020201 artificial intelligence & image processing
Artificial intelligence
business
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
- Accession number :
- edsair.doi.dedup.....be1e1c21f8771df09deffd3dc3c66979