|"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]|
|"Self-organizing Cascaded Structure of Deformable Part Models for Fast Object Detection", in IEEE Int. Conf. on Pattern Recognition (ICPR), 2014.|
|"Motion Interaction Field for Accident Detection in Traffic Surveillance Video", in IEEE Int. Conf. on Pattern Recognition (ICPR), 2014.|
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|