Improving the performance of k-means for color quantization
Image and Vision Computing
Arcimboldo-like collage using internet images
Proceedings of the 2011 SIGGRAPH Asia Conference
Color quantization using modified artificial fish swarm algorithm
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
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This paper presents a new stylized augmented reality (AR) framework which can generate line drawing and abstracted shading styles. In comparison with the state-of-art work, our framework can significantly improve both the visual immersion of a single frame and the temporal coherence of augmented video streams in real time. In our framework, we first render virtual objects over the input camera images and then uniformly process the combined contents with stylization techniques. For generating line drawing stylization, we first propose a specially designed shading method to render the virtual objects, and then use an adapted Flow-based anisotropic Difference-of-Gaussion (FDoG) filter to yield the high-quality line drawing effect. For generating the abstracted stylization, a focus-guided diffusion filter and a soft color quantization operator are sequentially applied to the augmented image, and then the processed result is combined with the detected edges to produce the final abstraction effect. The presented algorithms are all sympathetic to highly parallel processing, allowing a real-time performance on contemporary graphics hardware.