Dynamic Texture with Fourier Descriptors

By Bobby Abraham, Octavia I. Camps, Mario Sznaier. 2005

44 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Dacheng Tao
2. Sabine Süsstrunk
3. José Carlos Príncipe
4. Xinge You
5. Luciano Sbaiz
6. Roberto Costantini
7. Luc Van Gool
8. Ming-Hsuan Yang

Citations in the corpus

• Learning Energy-Based Spatial-Temporal Generative ConvNets for Dynamic Patterns (2019, neutral): “We compare our method with some baseline methods for dynamic textures, such as HOSVD [69], FFT-LDS [70], and Doretto et al. [1], in terms of SSIM on 17 dynamic texture videos in Table 1.”
• Cooperative Training of Descriptor and Generator Networks (2016, neutral): “, LDS [69], FFT-LDS [71], MKGPDM [72], and”
• Kernel Learning for Dynamic Texture Synthesis (2016, methodology): “Moreover, physical model generation is time consuming and computationally expensive, and complicated physical models may introduce unwanted texture artifacts, that make the final result less photorealistic [17].”
• Higher Order SVD Analysis for Dynamic Texture Synthesis (2008, methodology): “Finally, Section VI concludes the article.”