Three-dimensional object recognition
ACM Computing Surveys (CSUR) - Annals of discrete mathematics, 24
Image Analysis Using Mathematical Morphology
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Curvature-Based Approach to Terrain Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fourier array imaging
Automatic Detection of Human Nudes
International Journal of Computer Vision - 1998 Marr Prize
Probabilistic Methods for Finding People
International Journal of Computer Vision
3-D Human Modeling and Animation
3-D Human Modeling and Animation
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Visualizing the non-visual: spatial analysis and interaction with information from text documents
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
Rapid detection of significant spatial clusters
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Feature hiding in 3D human body scans
Information Visualization - Special issue on visual analysis of human dynamics
Digital Straight Line Segments
IEEE Transactions on Computers
A privacy algorithm for 3d human body scans
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
ADWICE – anomaly detection with real-time incremental clustering
ICISC'04 Proceedings of the 7th international conference on Information Security and Cryptology
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Visual privacy is a sensitive subject because it literally deals with human private parts. It presents a bold challenge to the field of Computer Science. The goal of this study is to build a virtual human model for designing and evaluating visual privacy technologies before a security system is built. Given the available databases of anthropological models from CAESAR, 3D scanners and the physical parameters of human imaging systems, we simulate the scanning imagery data with the High Frequency Structure Simulator (HFSS). The proportion and template matching algorithms have been developed to find the human surface features from 3D scanning data. The concealed object detection algorithms are developed according to the wave intensity and surface characteristics. Then the privacy-aware rendering methods are evaluated by usability studies. This forward-thinking approach intends to transform the development of visual privacy technologies from device-specific and proprietary to device-independent and open source. It also advances privacy research from an ad-hoc problem-solving process to a systematic design process, enabling multi-disciplinary innovations in digital human modeling, computer vision, information visualization, and computational aesthetics. The results of this study can be used in the privacy-aware imaging systems in airports and medical systems. They can also benefit the custom-fit products that are designed from personal 3D scanning data. Furthermore, our results can be used in the reconstruction of objects in digital archeology and medical imaging technologies such as virtual colonoscopy.