Title :
A Study on Visible to Infrared Action Recognition
Author :
Yu Zhu ; Guodong Guo
Author_Institution :
Lane Dept. of Comput. Sci. & Electr. Eng., West Virginia Univ., Morgantown, WV, USA
Abstract :
Human action recognition is important in image and video processing with many applications. With the development of sensor technology, different cameras can be used for action acquisition, e.g., infrared cameras. Is it possible to adapt the visible light action recognizers to a new modality or domain? In this paper, we study the feasibility to adapt the action recognizer learned from visible light spectrum to infrared. A preliminary result is obtained on a large database based on an adaptive learning method, demonstrating the potential to perform cross-spectral action recognition.
Keywords :
cameras; image motion analysis; learning (artificial intelligence); support vector machines; action acquisition; adaptive learning method; cross-spectral action recognition; human action recognition; image processing; infrared action recognition; infrared cameras; sensor technology; video processing; visible action recognition; visible light action recognizers; visible light spectrum; Cameras; Databases; Feature extraction; Linear programming; Spatiotemporal phenomena; Support vector machines; Training; Action recognition; adaptive support vector machines; correlation; cross-spectrum; infrared; visible light;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2013.2272920
