User oriented language model for face detection

Daesik Jang, G. Miller, S. Fels, S. Oldridge
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引用次数: 19

Abstract

This paper provides a novel approach for a user oriented language model for face detection. Even though there are many open source or commercial libraries to solve the problem of face detection, they are still hard to use because they require specific knowledge on details of algorithmic techniques. This paper proposes a high-level language model for face detection with which users can develop systems easily and even without specific knowledge on face detection theories and algorithms. Important conditions are firstly considered to categorize the large problem space of face detection. The conditions identified here are then represented as expressions in terms of a language model so that developers can use them to express various problems. Once the conditions are expressed by users, the proposed associated interpreter interprets the conditions to find and organize the best algorithms to solve the represented problem with corresponding conditions. We show a proof-of-concept implementation and some test and analyze example problems to show the ease of use and usability.
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面向用户的人脸检测语言模型
本文提出了一种面向用户的人脸检测语言模型。尽管有许多开源或商业库来解决人脸检测问题,但它们仍然很难使用,因为它们需要对算法技术的细节有专门的了解。本文提出了一种用于人脸检测的高级语言模型,用户可以使用该模型轻松开发系统,甚至不需要特定的人脸检测理论和算法知识。首先考虑重要条件,对人脸检测的大问题空间进行分类。这里确定的条件然后用语言模型表示为表达式,以便开发人员可以使用它们来表示各种问题。一旦用户表达了条件,所提出的关联解释器对条件进行解释,找到并组织最佳算法,用相应的条件来解决所表示的问题。我们展示了一个概念验证实现和一些测试和分析示例问题,以显示易用性和可用性。
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