NIST自动视频分析评估方向

J. Garofolo
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引用次数: 0

摘要

NIST从2001年开始对视频信息的自动分析进行了一系列的评估。这些开始于NIST文本检索评估(TREC),作为在大量视频集合中搜索信息的试点。评估系列被分拆成自己的评估/研讨会系列,称为TRECVID。TRECVID继续研究为搜索技术提取特征所面临的挑战。2004年,NIST还开始了一个评估系列,致力于评估视频目标检测和跟踪技术,使用的训练和测试集比过去使用的要大得多,这促进了新的机器学习方法,并支持统计信息的评估结果。最终,这项工作与欧洲在事件、活动和关系分类(CLEAR)联盟下实施的其他视频处理评估合并在一起。NIST的目标是将这些视频处理技术的评估发展为关注视觉可观察事件的检测和3D建模,并帮助计算机视觉社区在准确性、鲁棒性和效率方面取得进展。
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Directions in automatic video analysis evaluations at NIST
NIST has been conducting a series of evaluations in the automatic analysis of information in video since 2001. These began within the NIST text retrieval evaluation (TREC) as a pilot track in searching for information in large collections of video. The evaluation series was spun off into its own evaluation/workshop series called TRECVID. TRECVID continues to examine the challenge of extracting features for search technologies. In 2004, NIST also began an evaluation series dedicated to assessing video object detection and tracking technologies using training and test sets that were significantly larger than those used in the past -facilitating novel machine learning approaches and supporting statistically-informative evaluation results. Eventually this effort was merged with other video processing evaluations being implemented in Europe under the classification of events, activities, and relationships (CLEAR) consortium. NIST's goal is to evolve these evaluations of video processing technologies towards a focus on the detection of visually observable events and 3D modeling and to help the computer vision community make strides in the areas of accuracy, robustness, and efficiency.
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