- Image/Video Storage, Retrieval
- Image/Video Processing
- Image/Video Coding
- Image Scanning, Display, and Printing
- Image Formation
- Read more about Face Image Quality Assessment for Face Selection in Surveillance Video using Convolutional Neural Networks
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1570165667.pdf
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- Read more about Eccentricity Effect of Motion Silencing on Naturalistic Videos
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- Read more about Locally Linear Low-rank Tensor Approximation
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- Read more about Edge Preserving Multiscale Image Decomposition with Customized Domain Transform Filters
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In this paper, a multiscale image decomposition method based on domain transform is proposed. The domain transform is a high speed edge preserving smoothing method and can be used to many image processing applications. However, it is highly sensitive to noise. The proposed method is based on filters used in the domain transform but is designed to be robust to noise by employing a multiscale method. An optimization problem is formulated to obtain desired domain- transformed output. As expected, the method can be used to many applications as the domain transform.
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- Read more about Simulation of grain growth in polycrystalline materials: A signal processing perspective
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- Read more about Globalized BM3D using fast eigenvalue filtering
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In this work, we propose an improved fast multiple-view image denoising algorithm using 3D focus image stacks. It showed improved computational efficiency and comparable denoising quality compared to conventional methods.
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Presentation slides covering:
- robust foreground detection / background subtraction via patch-based analysis
- person re-identification based on representations on Riemannian manifolds
- robust object tracking via Grassmann manifolds
- adapting the lessons from big data to computer vision
- future paradigm shifts: computer vision based on networks of neurosynaptic cores
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Slides from the Tutorial on Riemannian Geometry in Computer Vision, presented at the Asian Conference on Computer Vision (ACCV), Singapore, 2014.
The slides show (1) how objects can be interpreted as points on Riemannian and Grassmann manifolds, and (2) various distance measures on manifolds. Demonstrates usefulness of manifold techniques in applications such as object tracking and person re-identification.
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