基于内容的视频情感语义分析关键技术研究
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摘要
随着多媒体技术的不断发展,数字视频近年来逐渐成为信息记录和传播的一种重要方式。传统的人工标注方法不能适应急速增长的视频数据分类和检索需求。在这种情况下,人们开始研究基于内容的视频语义分析技术,希望通过建立视频低层物理特征空间和高层语义空间的映射关系,从视频内容中提取能反映人类主观概念中的语义信息,自动对视频语义内容进行标注。情感语义是视频中最高层的语义信息,如何提取和描述视频所表达的情感语义信息是目前视频语义分析中重要研究方向之一。
基于内容的视频情感语义分析有很高的技术综合性,其主要的关键技术包括情感语义模型构建、认知层语义分析技术、情感层语义分析技术以及基于情感内容的视频检索技术等,本文在这几方面做了深入的分析和研究,所做工作及主要创新成果如下：
(1)设计了一种新的情感空问模型。根据情感产生的基本原理以及视频情感信息的特点,用“情感直方图”的方式来表达视频情感空间。该模型能够有效地进行情感类型描述和情感强度表达。
(2)设计了一种基于本体论的视频情感语义分析框架。根据视频语义内容呈现的基本规律和本体论的研究成果,对视频本体的概念进行了定义,建立了一套函数体系和推理关系,并根据此框架设计了视频情感语义分析的整体流程。
(3)提出了一套认知层语义分析的算法,认知层语义分析是情感识别的基础和重要步骤,本文对认知层语义分析中的视频对象分割算法、视频对象识别分类算法以及对象运动轨迹检测算法进行了研究,提出了一套改进的算法并进行了对比分析。
(4)提出了视频“情感语义对象”的概念,分析了人类视觉系统(HVS)的注意机制,对视频内能够引起人们注意并产生情感反应的主要对象进行了识别和判定。将人工神经网络技术引入视频情感分析领域,构建了一种从认知层语义到情感层语义的映射模型。
(5)设计了一套基于情感内容的视频检索系统,利用面向对象技术和关系型数据库技术,将视频分析获取的情感层语义内容采用结构化的方式进行存储和组织,提供有效的用户接口实现基于情感内容的视频检索。
With the continuous development of multimedia technology, digital video in recent years has gradually become an important way of information documentation and dissemination. The traditional manual annotation methods can not adapt to the rapid growth of video data classification and retrieval needs. In this case, people began to study the content-based video semantic analysis technology, through the establishment of the video low-level physical characteristics of space and high-level semantic space mapping, obtain the video semantic content description of video automatically. Extracted from the video content can reflect the human subjective concept of semantic information, how to describe the emotion expressed by the video information are becoming the new focus of the video content analysis, is one of the important research directions in the video content analysis.
Content-based video emotional semantic analysiscombines a number of technologies, the major critical technologies including emotional semantic modeling, cognitive level semantic analysis, emotional layer semantic analysis and the emotional content-based video retrieval technique, this paperthese aspects in-depth analysis and research, the work done and the major innovations are as follows:
(1) Design a new emotional space model.By the basic theory and the video characteristics of emotional information, usingemotional histogram way to express the emotions generated video emotional space, the model can effectively carry out the description of the emotional type and emotionalintensity of expression.
(2) Design ontology-based video emotionalsemantic analysis framework.By the basic law of semantic content presented in the video and the research results of the ontology, this paper deifned the concept of the video ontology, and built a function system and reasoning relations. According to this framework,this paperdesign a video emotional semantic analysis of the overall process.
(3) Proposed a cognitive level semantic analysis algorithms, cognitive level semantic analysis is an important step of the emotion recognition, the cognitive level semantic analysis include video object segmentation algorithm, the classification algorithm of video object recognition and object tracking algorithm, the study proposed a set of improved algorithms and thus a comparative analysis.
(4) Proposed the concept of the video "emotional semantic object". This paper analyzes the human visual system (HVS) attention mechanisms, and to draw attention and generate emotional response to the main object identification to determine the video. Artificial neural network technology into the video field of sentiment analysis, and constructed a set of semantics from a cognitive layer to the emotional layer of semantic mapping model.
(5) Designed a set of emotional content-based video retrieval system. Using object-oriented technology and relational database technology, the semantic content of the video analysis to obtain the emotional layer structured way to store and organize, to provide an effective user interface search video affective content.
基于内容的视频情感语义分析有很高的技术综合性,其主要的关键技术包括情感语义模型构建、认知层语义分析技术、情感层语义分析技术以及基于情感内容的视频检索技术等,本文在这几方面做了深入的分析和研究,所做工作及主要创新成果如下：
(1)设计了一种新的情感空问模型。根据情感产生的基本原理以及视频情感信息的特点,用“情感直方图”的方式来表达视频情感空间。该模型能够有效地进行情感类型描述和情感强度表达。
(2)设计了一种基于本体论的视频情感语义分析框架。根据视频语义内容呈现的基本规律和本体论的研究成果,对视频本体的概念进行了定义,建立了一套函数体系和推理关系,并根据此框架设计了视频情感语义分析的整体流程。
(3)提出了一套认知层语义分析的算法,认知层语义分析是情感识别的基础和重要步骤,本文对认知层语义分析中的视频对象分割算法、视频对象识别分类算法以及对象运动轨迹检测算法进行了研究,提出了一套改进的算法并进行了对比分析。
(4)提出了视频“情感语义对象”的概念,分析了人类视觉系统(HVS)的注意机制,对视频内能够引起人们注意并产生情感反应的主要对象进行了识别和判定。将人工神经网络技术引入视频情感分析领域,构建了一种从认知层语义到情感层语义的映射模型。
(5)设计了一套基于情感内容的视频检索系统,利用面向对象技术和关系型数据库技术,将视频分析获取的情感层语义内容采用结构化的方式进行存储和组织,提供有效的用户接口实现基于情感内容的视频检索。
With the continuous development of multimedia technology, digital video in recent years has gradually become an important way of information documentation and dissemination. The traditional manual annotation methods can not adapt to the rapid growth of video data classification and retrieval needs. In this case, people began to study the content-based video semantic analysis technology, through the establishment of the video low-level physical characteristics of space and high-level semantic space mapping, obtain the video semantic content description of video automatically. Extracted from the video content can reflect the human subjective concept of semantic information, how to describe the emotion expressed by the video information are becoming the new focus of the video content analysis, is one of the important research directions in the video content analysis.
Content-based video emotional semantic analysiscombines a number of technologies, the major critical technologies including emotional semantic modeling, cognitive level semantic analysis, emotional layer semantic analysis and the emotional content-based video retrieval technique, this paperthese aspects in-depth analysis and research, the work done and the major innovations are as follows:
(1) Design a new emotional space model.By the basic theory and the video characteristics of emotional information, usingemotional histogram way to express the emotions generated video emotional space, the model can effectively carry out the description of the emotional type and emotionalintensity of expression.
(2) Design ontology-based video emotionalsemantic analysis framework.By the basic law of semantic content presented in the video and the research results of the ontology, this paper deifned the concept of the video ontology, and built a function system and reasoning relations. According to this framework,this paperdesign a video emotional semantic analysis of the overall process.
(3) Proposed a cognitive level semantic analysis algorithms, cognitive level semantic analysis is an important step of the emotion recognition, the cognitive level semantic analysis include video object segmentation algorithm, the classification algorithm of video object recognition and object tracking algorithm, the study proposed a set of improved algorithms and thus a comparative analysis.
(4) Proposed the concept of the video "emotional semantic object". This paper analyzes the human visual system (HVS) attention mechanisms, and to draw attention and generate emotional response to the main object identification to determine the video. Artificial neural network technology into the video field of sentiment analysis, and constructed a set of semantics from a cognitive layer to the emotional layer of semantic mapping model.
(5) Designed a set of emotional content-based video retrieval system. Using object-oriented technology and relational database technology, the semantic content of the video analysis to obtain the emotional layer structured way to store and organize, to provide an effective user interface search video affective content.
引文
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