Time-slice analysis of dyadic human activity

La reconnaissance d’activités humaines à partir de données vidéo est utilisée pour la surveillance ainsi que pour des applications d’interaction homme-machine. Le principal objectif est de classer les vidéos dans l’une des k classes d’actions à partir de vidéos entièrement observées. Cependant, de tout temps, les systèmes intelligents sont améliorés afin de prendre des décisions basées sur des incertitudes et ou des informations incomplètes. Ce besoin nous motive à introduire le problème de l’analyse de l’incertitude associée aux activités humaines et de pouvoir passer à un nouveau niveau de généralité lié aux problèmes d’analyse d’actions. Nous allons également présenter le problème de reconnaissance d’activités par intervalle de temps, qui vise à explorer l’activité humaine dans un intervalle de temps court. Il a été démontré que l’analyse par intervalle de temps est utile pour la caractérisation des mouvements et en général pour l’analyse de contenus vidéo. Ces études nous encouragent à utiliser ces intervalles de temps afin d’analyser l’incertitude associée aux activités humaines. Nous allons détailler à quel degré de certitude chaque activité se produit au cours de la vidéo. Dans cette thèse, l’analyse par intervalle de temps d’activités humaines avec incertitudes sera structurée en 3 parties. i) Nous présentons une nouvelle famille de descripteurs spatiotemporels optimisés pour la prédiction précoce avec annotations d’intervalle de temps. Notre représentation prédictive du point d’intérêt spatiotemporel (Predict-STIP) est basée sur l’idée de la contingence entre intervalles de temps. ii) Nous exploitons des techniques de pointe pour extraire des points d’intérêts afin de représenter ces intervalles de temps. iii) Nous utilisons des relations (uniformes et par paires) basées sur les réseaux neuronaux convolutionnels entre les différentes parties du corps de l’individu dans chaque intervalle de temps. Les relations uniformes enregistrent l’apparence locale de la partie du corps tandis que les relations par paires captent les relations contextuelles locales entre les parties du corps. Nous extrayons les spécificités de chaque image dans l’intervalle de temps et examinons différentes façons de les agréger temporellement afin de générer un descripteur pour tout l’intervalle de temps. En outre, nous créons une nouvelle base de données qui est annotée à de multiples intervalles de temps courts, permettant la modélisation de l’incertitude inhérente à la reconnaissance d’activités par intervalle de temps. Les résultats expérimentaux montrent l’efficience de notre stratégie dans l’analyse des mouvements humains avec incertitude.Recognizing human activities from video data is routinely leveraged for surveillance and human-computer interaction applications. The main focus has been classifying videos into one of k action classes from fully observed videos. However, intelligent systems must to make decisions under uncertainty, and based on incomplete information. This need motivates us to introduce the problem of analysing the uncertainty associated with human activities and move to a new level of generality in the action analysis problem. We also present the problem of time-slice activity recognition which aims to explore human activity at a small temporal granularity. Time-slice recognition is able to infer human behaviours from a short temporal window. It has been shown that temporal slice analysis is helpful for motion characterization and for video content representation in general. These studies motivate us to consider timeslices for analysing the uncertainty associated with human activities. We report to what degree of certainty each activity is occurring throughout the video from definitely not occurring to definitely occurring. In this research, we propose three frameworks for time-slice analysis of dyadic human activity under uncertainty. i) We present a new family of spatio-temporal descriptors which are optimized for early prediction with time-slice action annotations. Our predictive spatiotemporal interest point (Predict-STIP) representation is based on the intuition of temporal contingency between time-slices. ii) we exploit state-of-the art techniques to extract interest points in order to represent time-slices. We also present an accumulative uncertainty to depict the uncertainty associated with partially observed videos for the task of early activity recognition. iii) we use Convolutional Neural Networks-based unary and pairwise relations between human body joints in each time-slice. The unary term captures the local appearance of the joints while the pairwise term captures the local contextual relations between the parts. We extract these features from each frame in a time-slice and examine different temporal aggregations to generate a descriptor for the whole time-slice. Furthermore, we create a novel dataset which is annotated at multiple short temporal windows, allowing the modelling of the inherent uncertainty in time-slice activity recognition. All the three methods have been evaluated on TAP dataset. Experimental results demonstrate the effectiveness of our framework in the analysis of dyadic activities under uncertaint

A new framework of human interaction recognition based on multiple stage probability fusion

Visual-based human interactive behavior recognition is a challenging research topic in computer vision. There exist some important problems in the current interaction recognition algorithms, such as very complex feature representation and inaccurate feature extraction induced by wrong human body segmentation. In order to solve these problems, a novel human interaction recognition method based on multiple stage probability fusion is proposed in this paper. According to the human body’s contact in interaction as a cut-off point, the process of the interaction can be divided into three stages: start stage, execution stage and end stage. Two persons’ motions are respectively extracted and recognizes in the start stage and the finish stage when there is no contact between those persons. The two persons’ motion is extracted as a whole and recognized in the execution stage. In the recognition process, the final recognition results are obtained by the weighted fusing these probabilities in different stages. The proposed method not only simplifies the extraction and representation of features, but also avoids the wrong feature extraction caused by occlusion. Experiment results on the UT-interaction dataset demonstrated that the proposed method results in a better performance than other recent interaction recognition methods

A new framework of human interaction recognition based on multiple stage probability fusion

Visual-based human interactive behavior recognition is a challenging research topic in computer vision. There exist some important problems in the current interaction recognition algorithms, such as very complex feature representation and inaccurate feature extraction induced by wrong human body segmentation. In order to solve these problems, a novel human interaction recognition method based on multiple stage probability fusion is proposed in this paper. According to the human body’s contact in interaction as a cut-off point, the process of the interaction can be divided into three stages: start stage, execution stage and end stage. Two persons’ motions are respectively extracted and recognizes in the start stage and the finish stage when there is no contact between those persons. The two persons’ motion is extracted as a whole and recognized in the execution stage. In the recognition process, the final recognition results are obtained by the weighted fusing these probabilities in different stages. The proposed method not only simplifies the extraction and representation of features, but also avoids the wrong feature extraction caused by occlusion. Experiment results on the UT-interaction dataset demonstrated that the proposed method results in a better performance than other recent interaction recognition methods

Here in the To-Day, Forgotten in the To-Morrow: Re-covering and Re-membering the Feminist Rhetorics of 19-Century Actress and Author Adah Menken

This dissertation project, which recovers the feminist invention of 19th-century actress and author Adah Menken, proves the efficacy of conducting historigraphic recoveries of heretofore forgotten and elided female rhetors. I situate Adah’s visual and written performances within the materiality of Victorian social codes, positioning her as a feminist commentator worthy of inclusion in our remembrances of feminist discourses. I use archival sources including carte de visites (CDVs) and Adah’s letters and poetry as heuristics for gendered critique, to analyze how she resisted the master narrative of Victorian society and its accompanying codes governing public and private feminine behavior. My objectives are three-fold: to use archival recovery as a method to unearth and evaluate what feminist inquiry can accomplish; to argue for the feminist intentions of a previously unknown female writer; and to offer an opportunity to discover cross-disciplinary connections for rhetorical recoveries. Feminist inquiry is itself an exemplar of rhetorical invention, the idea of making a path. In my dissertation project, I illustrate how Adah Menken blazed a path in her personal and public rhetorics. For my principal goal of asserting Adah’s importance as a feminist rhetor, I use primary sources to demonstrate that her invention and resistance provide fertile ground for vital feminist inquiry. As a secondary means of asserting the significance of archival feminist research, I also offer my Adah Menken recovery as a case study for examining ideas of resistance and subversion to dominant master narratives. For this application, I use Judith Butler’s theory of performativity and Michel Foucault’s ideas surrounding the topic of resistance. Ultimately, the convergence of theoretical and practical applications for rhetorical recoveries, both of which I describe in-depth in my dissertation, serve to re-connect fields of inquiry and make them relevant to scholars across the Academe

John Browne's 'Treatise of the Muscles' (1681) and the Image of Mobility in late seventeenth-century London

In late seventeenth-century London, anatomists, artists, actors and print collectors studied images of the moving, muscular body. John Browne’s Treatise of the Muscles (1681) includes anatomical plates that display the intersection between different types of bodily knowledge within this period. Browne’s images can be read as part of a genealogy of traditional anatomical visual production and yet they include contemporary postures, gestures and fashionable accoutrements such as canes and wigs. As such they can be understood alongside alternative, supplementary imagery, including conduct manuals, fashion plates, artist’s drawing books and architectural plans. Exploring these less familiar precedents and isolating new trajectories for the anatomical image serves to temper scholarly narratives that focus upon the ‘bloody spectacle’ of the dissection theatre. Instead, the focus upon this anatomical treatise, presents us with a set of images through which to investigate the social body of the seventeenth-century user of such texts. The way that Browne’s plates convey knowledge of the muscular structure indicates that the potential use value of these images is in excess of the practical field of medical study. Browne’s figures embody seventeenth- century notions of Restoration sovereignty, courtesy and civility, characterised in a dialogue between macrocosmic social order and micro- muscular mechanical control. In the chapters of this dissertation Browne’s bodies are considered alongside three different contexts of cultural production: the discernibly fashionable body, the artifice and illusion of the playhouse and the muscular system imagined as sculptural form. This thesis, in the broadest terms, is an examination of the repaired, post-Restoration, public muscular body that required study and care to remain elegant and civil. Following the trail of the animated anatomical body through a broad array of visual material demonstrates the complexity – and pleasure – of viewing muscular representation at a specific historical moment in London

Early Literacy Practices and Beliefs About Education Among Hispanic Families in Jacksonville, Florida

Hispanic children in the United States are more likely to fall behind in several literacy measures even before they enroll in prekindergarten programs. There are some structural and non-structural factors that have a direct impact on Hispanic children’s early literacy skills. Among the non-structural factors this mixed-method study explored Hispanic caregivers’ beliefs about education as well as their literacy practices at home. The study compared two groups: diverse Hispanic caregivers with 4-year-old children enrolled in the Voluntary Prekindergarten Program (VPK) and diverse Hispanic caregivers whose 4-year-old children were not enrolled in VPK. A total of 125 diverse Hispanic caregivers responded to two surveys: the Parental Reading Belief Inventory and the Adaptation of the Stony Brooks Reading Survey. Twenty Hispanic parents were later interviewed to better understand their beliefs about education as well as their literacy practices at home. The surveys and interviews revealed playing games, drawing pictures and looking at books with their children were the most common literacy practices in which Hispanic caregivers engaged. All participants in the study stated how much they value their children’s education. Some, particularly caregivers whose children were participating in VPK programs, were more likely to engage in their children’s education and experience fewer barriers to reading at home. Country of origin played an important role in differentiating Hispanic parents in their beliefs about education as well as in their literacy practices at home. From the diverse group of participants in the study, Mexican caregivers were less likely to perceive themselves as playing a key role in their children’s education and they also shared experiencing more barriers in their literacy activities when compared with parents from Cuba and Puerto Rico. Overall, enrollment in VPK was dependent upon the type of barriers to reading activities that Hispanic parents experience as well their country of origin

Logic of Experimentation

"Beyond interpretation: a proposal for experimental performance practices Logic of Experimentation offers several innovative and ground-breaking perspectives on music performance, music ontology, research methodologies and ethics of performance. It proposes new modes of thinking and exposing past musical works to contemporary audiences, arguing for a new kind of performer, emancipated from authoritative texts and traditions, whose creativity is propelled by intensive research and inventive imagination. Moving beyond the work-concept, Logic of Experimentation presents a new image of musical works, based upon the notions of strata, assemblage and diagram, advancing innovative practice-based methodologies that integrate archival and musicological research into the creative process leading to a performance. Beyond representational modes of performance—be it mainstream or historically informed performance practices—Logic of Experimentation creates an ontological, methodological and ethical space for experimental performance practices, arguing for a new mode of performance. Written in an experimental style, its eight chapters appropriate music performance concepts from post-structural philosophy, psychoanalysis, science and technology studies, epistemology and semiotics, displaying how transdisciplinarity is central to artistic research. An indispensable contribution to artistic research in music, Logic of Experimentation is compelling reading for music performers, composers, musicologists, philosophers and artist researchers alike.