非擬真著色(Non-photorealistic Rendering, NPR)在電腦圖學領域中已發展一段時間，至今已發展出許多不同的藝術風格，並應用在各個領域。相對於擬真著色(Photorealistic Rendering, PR)講求細節與寫實度，非擬真著色的演算較著重藝術感與呈現手法，其輸出結果也較為簡潔。

在非擬真著色的應用中，大部分的研究著重於靜態的影像處理，其輸出結果亦是靜態的影像。而關於影片處理的研究則相對較少，且大多是對整個畫面做非擬真著色處理，對局部的處理則更是少見。

本研究提供了一套互動式的影片非擬真著色系統。不同於一般的影片處理，本系統以局部處理為目標，不事先進行資料訓練或依靠其他輔助設備，僅根據使用者所選擇的物件線索，自動追蹤影片中的物件。本系統可讓使用者自由選取欲處理的物件，並藉由NVidia的CUDA模組，以GPU運算與降解析度(Down Sampling)達到即時處理(Real-time)，此技術可應用於擴增實境(Augmented Reality, AR)。

Non-photorealistic rendering (NPR) has been developed in the computer graphics field for a while. There are lots of different kinds of artistic styles and various applications. Different from Photorealistic rendering (PR), which focuses on detail and realism, NPR's algorithm emphasizes the sense of art and presentation, the output result is much simpler.

Most of prior researches apply NPR on static images. The research of applying NPR on a video is rarely found, while most of them process the entire frame instead of part of a frame.
Our research provided a system of video non-photorealistic rendering via interactive object selection.
Different from general video processing, our system aims to process the selected object which is not automatically tracked by doing information training or depending on other auxiliary facilities, but rely on the clue from user's selection.

A user can choose any item to be process, and achieve a real-time processing with GPU calculation through NVidia's CUDA module.
This method can also be used on Augmented Reality (AR).

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