應用於車內視訊之光線適應性視訊壓縮編碼器設計; An Illumination Adaptive Video Coding Scheme for In-vehicle Video Applications

NCUIR > College of Electrical Engineering & Computer Science > Graduate Institute of Communication Engineering > Electronic Thesis & Dissertation > Item 987654321/8243

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/8243

Title:	應用於車內視訊之光線適應性視訊壓縮編碼器設計;An Illumination Adaptive Video Coding Scheme for In-vehicle Video Applications
Authors:	賴學翰;Hsueh-Han Lai
Contributors:	通訊工程研究所
Keywords:	車內視訊;光線;視訊壓縮;in-vehicle;video coding;illumination
Date:	2008-06-16
Issue Date:	2009-09-22 11:21:49 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	本論文設計一個提高乘客方便性之視訊通訊，可應用於車內駕駛人或乘客與辦公室內或是搭乘交通工具中的人之視訊通訊。但因為在無線通訊傳輸頻寬有限，所以此系統設計考量人類視覺特性的視訊編碼，降低非人臉區域的資料量。另一方面，由於光線常因環境的變化而改變，進而造成車內視訊內容有顯著的改變。因此，在此論文中，我們提出應用於車內視訊之光線適應視訊壓縮編碼器，包含光線校正、人臉偵測以及和人類視覺注意力為基礎的視訊壓縮三個階段，而光線校正方案整合Single Scale Retinex 和間隔權重直方圖分割法。由實驗結果可知，我們的光線校正方案有效提高車內視訊的人臉偵測率。此外，我們的視訊壓縮系統不僅可以降低資料量，並同時保持良好之視訊品質。 With the advance of intelligent vehicle systems, drivers or passengers can keep interaction with people in fixed offices or other vehicles through visual communications. However, the illumination variations due to the changes of environments or weather conditions may significantly change the appearance of in-vehicle videos. Accordingly, the compression efficiency is much reduced even though the bandwidth of such wireless communications has been quite limited. There is pretty few previous work designed for efficient in-vehicle video compressions. Thus, in this paper, we propose an illumination adaptive video coding scheme for in-vehicle video applications. Since human faces are usually the most visually attended regions in such applications, this scheme consists of illumination correction, face detection, and the visual attention based video codec. The proposed illumination correction strategy combines the advantages of the single-scale Retinex (SSR) and the Interval weighted histogram separation (IWHS). The experimental results show that our illumination correction strategy effectively improves the face detection performance of in-vehicle videos. Moreover, the subjective visual quality of the proposed scheme outperforms that of H.264 with rate control since our scheme allocates bits by incorporating the human visual characteristics.
Appears in Collections:	[Graduate Institute of Communication Engineering] Electronic Thesis & Dissertation

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