IEEE CVPR 2011
TechTalks from event: IEEE CVPR 2011
Note: Award talks and user-uploaded contents are accessible for free. Other oral sessions are to be accessed by only those who registered for the main conference or for the webcast/video-proceedings. You can register to view video proceeding by visiting CVPR 2011 website and following the virtual-registration link.
Orals 3D Applications 3:30-5:10 Ballroom 2
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Separating Reflective and Fluorescent Components of An ImageColor plays a vitally important role in the world we live in. It surrounds us everywhere we go. Achromatic life, restricted to black, white and grey, is extremely dull. Color fascinates artists, for it adds enormously to aesthetic appreciation, directly invoking thoughts, emotions and feelings. Color fascinates scientists. For decades, scientists in color imaging, printing and digital photography have striven to satisfy increasing demands for accuracy in color reproduction. Fluorescence is a very common phenomenon observed in many objects such as gems and corals, writing paper, clothes, and even laundry detergent. Traditional color imaging algorithms exclude ?uorescence by assuming that all objects have only an ordinary re?ective component. The ?rst part of the thesis shows that the color appearance of an object with both re?ective and ?uorescent components can be represented as a linear combination of the two components. A linear model allows us to separate the two components using independent component analysis (ICA). We can then apply different algorithms to each component, and combine the results to form images with more accurate color. Displaying color images accurately is as important as reproducing color images accurately. The second part of the thesis presents a new, practical model for displaying color images on self-luminous displays such as LCD monitors. It shows that the model accounts for human visual system’s mixed adaptation condition and produces results comparable to many existing algorithms. -
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- All Sessions
- CVPR Award Papers
- Orals 1A Image and Video Retrieval - Ballroom 1 10:30-12:10
- Orals 1B Computational Photography - Ballroom 2 10:30-12:10
- Orals 1C Scene Understanding and 3D Structures - Ballroom 1 3:30-5:10
- Orals 1D Video Analysis - Ballroom 2 3:30 - 5:10
- Orals 2A Object Detection - 10:30-12:10 Ballroom 1
- Orals 2B - Optimization Methods - 10:30-12:10 Ballroom 2
- Orals 2C - Segmentation and Grouping - 3:30 -5:10 Ballroom 1
- Orals 2D - Motion and Tracking - 3:30-5:10 Ballroom 2
- Orals 3A Object Recognition - 10:30 - 12:10 Ballroom 1
- Orals 3B Image Modeling - 10:30 - 12:10 Ballroom 2
- Orals 3C Statistical Methods and Learning 3:30-5:10 Ballroom 1
- Orals 3D Applications 3:30-5:10 Ballroom 2
- CVPR Poster Session