Recognition of shiny dielectric objects by analysing the polarization of reflected light
Image and Vision Computing
Polarization-Based Material Classification from Specular Reflection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constraining Object Features Using a Polarization Reflectance Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Polarization methods in computer vision
Polarization methods in computer vision
Contrast Definition for Optical Coherent Polarimetric Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized Mosaicing: Polarization Panorama
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Estimation Using Polarization and Shading from Two Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-dimensional BRDF estimation from polarisation
Computer Vision and Image Understanding
ACM SIGGRAPH 2009 Courses
Surface material segmentation using polarisation
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
Natural material segmentation and classification using polarisation
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Reflection component separation using statistical analysis and polarisation
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Robust shape and polarisation estimation using blind source separation
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
3D reconstruction of metallic surfaces by photopolarimetric analysis
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Shape and Refractive Index from Single-View Spectro-Polarimetric Images
International Journal of Computer Vision
Robust estimation of shape and polarisation using blind source separation
Pattern Recognition Letters
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Overviewed are recent results of a new general approach to image understanding and computer vision utilizing the sensing of polarization of light. Whereas human vision is oblivious to components of light polarization, polarization parameters of light are shown to provide an important visual extension to intensity and color significantly expanding the application potential for image understanding. A physical state of polarization can be visualized directly in human terms as a particular hue and saturation, and this paper utilizes such a scheme presenting images of ordinary scenes as never seen before by humans in the domain of polarization vision. Metaphorically, humans are 'color blind' with respect to the perception of polarization, and even though this does not appear to inhibit human visual performance, we show how polarization vision is a sensory augmentation that can significantly enhance both automated image understanding and even possibly improve human visual performance itself under certain conditions. Sensors, calledpolarization cameras, have been developed that automatically sense components of partial linear polarization and computationally process these components to produce polarization images. Prototypes of different polarization camera sensors have been presented in earlier literature. A recent advancement in the design of polarization cameras has made it possible to interface low-cost modular components with almost any existing imaging device converting it into an automatic polarization camera. This compatibility with small portable imaging devices is making polarization imaging for the first time accessible to a number of application areas outside the laboratory, both outdoors and underwater, revealing polarization vision as a vast new visually augmented domain with unique capabilities. This paper presents various results from three on-going field applications: natural object recognition, inspection of ship hulls for damage, and marine biology.