Name
Abstract | ||
|---|---|---|
The advent of GPUs with programmable shaders on mobile phones has motivated developers to utilize GPU to offload computationally intensive tasks and relive the burden of embedded CPU. In this paper, we present a set of metrics to measure characteristics of a mobile phone GPU with the focus on image processing algorithms. These measures assist users in design and implementation stage and in classifying bottlenecks. We propose techniques to achieve increased performance with optimized shader design. To show the effectiveness of the proposed techniques, we employ cartoon-style non-photorealistic rendering (NPR), belief propagation (BP) stereo matching [Yang et al. 2006], and speeded up robust features (SURF) detection [Bay et al. 2008] as our example algorithms. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2037715.2037741 | SIGGRAPH Posters |
Keywords | Field | DocType |
embedded cpu,belief propagation,computationally intensive task,mobile phone gpu,image processing algorithm,optimized shader design,mobile phone,mobile gpu,cartoon-style non-photorealistic rendering,example algorithm,classifying bottleneck,image processing,video capture,computational photography,non photorealistic rendering | Computer vision,Video capture,Computer graphics (images),Computer science,Image processing,Time-of-flight camera,Artificial intelligence,Mobile phone,Shader,Rendering (computer graphics),Digital image processing,Belief propagation | Conference |
Citations | PageRank | References |
5 | 0.40 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nitin Singhal | 1 | 113 | 10.55 |
| Jin Woo Yoo | 2 | 32 | 1.78 |
| Ho Yeol Choi | 3 | 20 | 1.24 |
| In Kyu Park | 4 | 316 | 35.97 |