|"Robust and Fast Moving Object Detection in a Non-Stationary Camera via Foreground Probability based Sampling", IEEE International Conference on Image Processing (ICIP), 2015.|
|"User Interactive Segmentation with Partially Growing Random Forest", IEEE International Conference on Image Processing (ICIP), 2015.|
|"Learning with Adaptive Rate for Online Detection of Unusual Appearance", in 10th International Symposium on Visual Computing (ISVC'14), 2014|
|"Frequencygrams and Multi-Feature Joint Sparse Representation for Action and Gesture Recognition", in IEEE Int. Conf. on Image Processing (ICIP), 2014|
|"Audio Bank: A High-Level Acoustic Signal Representation for Audio Event Recognition", in IEEE Int. Conf. on control, automation and systems (ICCAS), 2014, [Best Presentation Award]|
The goal of the PILab is to gain useful technologies on perception and intelligence which can be applied to visual surveillance systems, inspection machines, robots, etc.
We are developing perceptual primitives to detect, track, and recognize human/vehicles, faces and to understand abnormal behaviors and situations through visual information. In addition, we are developing incremental learning models including probabilistic learning machines for integrating multiple sensory modalities in the changing environments.
Current topics that we are interested in :
|Computer vision journal list 2015|
|Computer Vision journal list|