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.本数据集包含120段经错误隐藏（Error Concealment, EC）处理的视频片段。这些片段源自6段CIF格式、6段高清（HD）及6段全高清（Full-HD）测试视频序列。每一段原始序列均采用4种错误隐藏技术进行处理：运动复制（Motion Copy）、运动向量外推（Motion Vector Extrapolation）、解码器运动向量估计（Decoder Motion Vector Estimation, DMVE）与边界匹配算法（Boundary Matching Algorithm, BMA）的组合方案，以及自适应错误隐藏顺序确定（Adaptive Error Concealment Order Determination, AECOD）。本数据集同时收录了原始无损失视频片段，以及附带错误隐藏视频主观质量排序结果的样本。构建该数据集的核心目的，是评估各类图像/视频质量评价（Image/Video Quality Assessment, I/VQA）方法的性能，即验证这些方法能否准确比对不同错误隐藏处理后视频的质量优劣。换言之，若某错误隐藏技术A生成的视频质量优于技术B，哪些I/VQA指标可以正确预测这一结果。更多详细信息可参阅以下论文：M. Kazemi、M. Ghanbari及S. Shirmohammadi，《评估错误隐藏视频质量的质量指标性能》（The Performance of Quality Metrics in Assessing Error-Concealed Video Quality），IEEE Transactions on Image Processing，第29卷，第5937-5952页，2020年。