Error-Concealed Video Dataset (ECVD)

This is a dataset of 120 error-concealed video clips. The clips were generated from 6 CIF, 6 HD and 6 Full-HD test video sequences. Each of those sequences was error concealed with 4 Error Concealment (EC) techniques: Motion Copy, Motion Vector Extrapolation, Decoder Motion Vector Estimation (DMVE) + Boundary Matching Algorithm (BMA), and Adaptive Error Concealment Order Determination (AECOD). The dataset also includes the original (loss free) video clips, as well as the subjective ranking of the error-concealed videos. The original purpose for generating this dataset is to evaluate the performance of various Image/Video Quality Assessment (I/VQA) methods in how well they compare the quality of error-concealed videos. In other words, if the output of EC technique A is a better-quality video than EC technique B, which I/VQA metric predicts this correctly.For more information please refer to the following paper:M. Kazemi, M. Ghanbari, and S. Shirmohammadi, “The Performance of Quality Metrics in Assessing Error-Concealed Video Quality,” IEEE Transactions on Image Processing, vol. 29, pp. 5937-5952, 2020.

本数据集由120个错误隐藏的视频片段组成。这些片段源自6个CIF、6个高清以及6个全高清的测试视频序列。每个序列均通过4种错误隐藏（EC）技术进行错误隐藏处理：运动复制、运动矢量外推、解码器运动矢量估计（DMVE）+ 边界匹配算法（BMA）以及自适应错误隐藏顺序确定（AECOD）。数据集还包括原始（无损）视频片段，以及错误隐藏视频的主观排名。生成本数据集的初衷是为了评估不同图像/视频质量评估（I/VQA）方法在比较错误隐藏视频质量方面的性能。换言之，若EC技术A输出的视频质量优于技术B，则哪个I/VQA指标能够准确预测这一结果。欲了解更多信息，请参阅以下论文：M. Kazemi, M. Ghanbari, and S. Shirmohammadi, “在评估错误隐藏视频质量中质量指标的效能，”IEEE图像处理 Transactions, 第29卷，第5937-5952页，2020年。