A COMPUTATION METHOD/FRAMEWORK FOR HIGH LEVEL VIDEO CONTENT ANALYSIS AND SEGMENTATION USING AFFECTIVE LEVEL INFORMATION

VIDEO segmentation facilitates e±cient video indexing and navigation in large digital video archives. It is an important process in a content-based video indexing and retrieval (CBVIR) system. Many automated solutions performed seg- mentation by utilizing information about the \facts" of the video. These \facts" come in the form of labels that describe the objects which are captured by the cam- era. This type of solutions was able to achieve good and consistent results for some video genres such as news programs and informational presentations. The content format of this type of videos is generally quite standard, and automated solutions were designed to follow these format rules. For example in [1], the presence of news anchor persons was used as a cue to determine the start and end of a meaningful news segment. The same cannot be said for video genres such as movies and feature films. This is because makers of this type of videos utilized different filming techniques to design their videos in order to elicit certain affective response from their targeted audience. Humans usually perform manual video segmentation by trying to relate changes in time and locale to discontinuities in meaning [2]. As a result, viewers usually have doubts about the boundary locations of a meaningful video segment due to their different affective responses. This thesis presents an entirely new view to the problem of high level video segmentation. We developed a novel probabilistic method for affective level video content analysis and segmentation. Our method had two stages. In the first stage, a®ective content labels were assigned to video shots by means of a dynamic bayesian 0. Abstract 3 network (DBN). A novel hierarchical-coupled dynamic bayesian network (HCDBN) topology was proposed for this stage. The topology was based on the pleasure- arousal-dominance (P-A-D) model of a®ect representation [3]. In principle, this model can represent a large number of emotions. In the second stage, the visual, audio and a®ective information of the video was used to compute a statistical feature vector to represent the content of each shot. Affective level video segmentation was achieved by applying spectral clustering to the feature vectors. We evaluated the first stage of our proposal by comparing its emotion detec- tion ability with all the existing works which are related to the field of a®ective video content analysis. To evaluate the second stage, we used the time adaptive clustering (TAC) algorithm as our performance benchmark. The TAC algorithm was the best high level video segmentation method [2]. However, it is a very computationally intensive algorithm. To accelerate its computation speed, we developed a modified TAC (modTAC) algorithm which was designed to be mapped easily onto a field programmable gate array (FPGA) device. Both the TAC and modTAC algorithms were used as performance benchmarks for our proposed method. Since affective video content is a perceptual concept, the segmentation per- formance and human agreement rates were used as our evaluation criteria. To obtain our ground truth data and viewer agreement rates, a pilot panel study which was based on the work of Gross et al. [4] was conducted. Experiment results will show the feasibility of our proposed method. For the first stage of our proposal, our experiment results will show that an average improvement of as high as 38% was achieved over previous works. As for the second stage, an improvement of as high as 37% was achieved over the TAC algorithm

Affect Analysis in Video

Ph.DDOCTOR OF PHILOSOPH

Can humain association norm evaluate latent semantic analysis?

This paper presents the comparison of word association norm created by a psycholinguistic experiment to association lists generated by algorithms operating on text corpora. We compare lists generated by Church and Hanks algorithm and lists generated by LSA algorithm. An argument is presented on how those automatically generated lists reflect real semantic relations

MOG 2007:Workshop on Multimodal Output Generation: CTIT Proceedings

This volume brings together presents a wide variety of work offering different perspectives on multimodal generation. Two different strands of work can be distinguished: half of the gathered papers present current work on embodied conversational agents (ECA’s), while the other half presents current work on multimedia applications. Two general research questions are shared by all: what output modalities are most suitable in which situation, and how should different output modalities be combined

On the conversation between female videobloggers and commentators

El desarrollo de YouTube como una plataforma social surge a partir de dos ideas. En primer lugar, los amateurs pueden producir contenido de cualquier índole. Y, en segundo lugar, su audiencia puede expresar su opinión sin restricciones. Este intercambio de información impulsa la formación de comunidades en torno a un interés común: contenido y/o videobloguero. La dimensión social en YouTube tiene lugar de manera bidireccional. La interacción regular entre las dos partes ha significado un cambio crucial en la percepción de la producción y consumo audiovisual, así como también en los productores de vídeo, amateurs y audiencia. Las investigaciones iniciales se han dirigido a examinar los comentarios independientemente de los rasgos conversacionales de los videoblogueros de YouTube. Sin embargo, hasta la fecha ningún trabajo se ha centrado en la conversación en YouTube. Así pues, esta monografía, en términos generales, persigue principalmente explorar el comportamiento comunicativo de la audiencia y de su videobloguero en YouTube basado en la co-dependencia, colaboración y convergencia de sus identidades interaccionales para producir una comunidad de YouTube. Por estas razones, el objetivo aquí es el análisis y entendimiento de la conversación dialógico y de la identidad conversacional de los usuarios de YouTube. Esto implica la combinación del análisis del discurso con un enfoque sociopsicológico, más precisamente una perspectiva sociolingüística interaccional. Por lo tanto, dada a la complejidad de los recursos comunicativos que YouTube ofrece, el estudio consiste en un análisis multimodal que incluye un conjunto de herramientas de otros análisis del discurso. Asimismo, una examinación cuantitativa trabaja junto con una perspectiva cualitativa siguiendo la teoría de la identidad social y sus subteorías. El material para el estudio incluye una colección de contenido de vídeo producido por las amateurs de belleza con mayor número de suscriptores en Gran Bretaña, y la compilación de los comentarios publicados en sus vídeos. Tras el análisis minucioso de la práctica comunicativa de los comunicadores de YouTube en los diferentes tipos de vídeos, los resultados muestran en primer lugar la utilización de una amplia variedad de recursos (no)lingüísticos como estrategias de presentación personal. En segundo lugar, demuestra la producción de identidades relacionales y multifacéticas que representan una disposición organizacional. En consecuencia, proporciona sugerencias sobre la contribución del diálogo para la creación de amateurs virtuales, sus seguidores y de una comunidad de práctica virtual. En resumen, las microcelebridades de YouTube y su consiguiente audiencia no son únicamente una práctica. Son más bien el resultado de su representación comunicativa interaccional en un contexto social y comunitario.The development of YouTube as a social platform is built on two assumptions. Firstly, amateurs can produce content of any nature. And, secondly, their viewership can express their opinion without restrictions. This exchange of information prompts the formation of communities around a common interest: the content or/and content creator. The social dimension on YouTube occurs bidirectionally. The consistent interaction between both parties has created a crucial change in the perception of audiovisual production and consumption as well as its impact on video producers, amateurs and audienceship. Early work has focused on online comments sections independently from the conversational cues of YouTube videobloggers. Yet, no research has been centred on the YouTube conversation so far. Therefore, this monograph, in broad terms, principally aims at delving into the communicative performance of the YouTube audience and their videoblogger based on the co-dependency, collaboration and convergence of their interactional identities to produce a YouTube community. Thereupon, the purpose here is the exploration and the understanding of the dialogic conversation on YouTube and the conversational identities of YouTube users. This involves the combination of discourse analysis with a sociopsychological approach, more precisely an interactional sociolinguistic approach.Thus, given the complexity of the communicative resources that YouTube offers, the study consists of a multimodal analysis including a toolkit of other discourse analyses. A quantitative examination works together with a qualitative approach following the social identity theory and its sub-theories. The data for the examination includes a collection of video-based content produced by the most-subscribed female beauty amateurs in Britain,and, the compilation of the comments posted in their videos. After a thorough examination of the communicative practice of YouTube communicators in the different types of videos, the findings show firstly the utilisation of a wide variety of (non)linguistic resources as self-presentation strategies. Secondly, it proves the production of relational and multifaceted identities which represent an organisational arrangement. Consequently, it provides hints on the contribution of the dialogue for the creation of online microcelebrities, their followership and of an online community of practice. In short, YouTube amateurs and their subsequent audienceship are not uniquely a performance. They are rather the result of their interactional communicative performance in a social and communal context

The Practical Science of Society

https://commons.und.edu/und-books/1107/thumbnail.jp

Nonverbal communication in depression

No abstract availabl