Kinship recognition is a challenging problem with many practical applications. With much progress and milestones having been reached after ten years - we are now able to survey the research and create new milestones. We review the public resources and data challenges that enabled and inspired many to hone-in on the views of automatic kinship recognition in the visual domain. The different tasks are described in technical terms and syntax consistent across the problem domain and the practical value of each discussed and measured. State-of-the-art methods for visual kinship recognition problems, whether to discriminate between or generate from, are examined. As part of such, we review systems proposed as part of a recent data challenge held in conjunction with the 2020 IEEE Conference on Automatic Face and Gesture Recognition. We establish a stronghold for the state of progress for the different problems in a consistent manner. This survey will serve as the central resource for the work of the next decade to build upon. For the tenth anniversary, the demo code is provided for the various kin-based tasks. Detecting relatives with visual recognition and classifying the relationship is an area with high potential for impact in research and practice.IEEE Transactions on pattern analysis and machine intelligence
翻译:承认亲子关系是一个具有挑战性的问题,有许多实际应用。随着十年后取得了许多进展和里程碑,我们现在能够对研究进行调查并创造新的里程碑。我们审查了公共资源和数据挑战,这些资源和数据挑战使许多人能够并激励他们了解视觉领域自动亲属承认的观点。不同的任务以技术术语和语法加以描述,在问题领域和每个讨论和计量的实际价值之间保持一致。审查视觉亲子承认问题的最新方法,无论是区别对待还是从中产生的问题。作为这些方法的一部分,我们审查了作为最近与2020年IEEEE自动脸和认知问题会议一起举行的数据挑战的一部分而提出的系统。我们以一致的方式为不同问题的进展状况建立了一个堡垒。这项调查将成为今后十年工作的核心资源。在十周年之际,为各种基于亲属的任务提供了《示范守则》。对有视觉识别和分类关系的亲属进行检测是研究和实践中具有很大影响的领域。IEEEEEE交易在模式分析和机器情报方面有着很大影响。