251 resultados para Face processing
Resumo:
Clustering identities in a video is a useful task to aid in video search, annotation and retrieval, and cast identification. However, reliably clustering faces across multiple videos is challenging task due to variations in the appearance of the faces, as videos are captured in an uncontrolled environment. A person's appearance may vary due to session variations including: lighting and background changes, occlusions, changes in expression and make up. In this paper we propose the novel Local Total Variability Modelling (Local TVM) approach to cluster faces across a news video corpus; and incorporate this into a novel two stage video clustering system. We first cluster faces within a single video using colour, spatial and temporal cues; after which we use face track modelling and hierarchical agglomerative clustering to cluster faces across the entire corpus. We compare different face recognition approaches within this framework. Experiments on a news video database show that the Local TVM technique is able effectively model the session variation observed in the data, resulting in improved clustering performance, with much greater computational efficiency than other methods.
Resumo:
Between the 1970s and the 1990s the level and type of emotionality in the Commonwealth Employment Service (the Australian national employment service) altered. Within a context of changing economic conditions and concomitant work intensification, it is argued that untenable working conditions resulted in new recruits adopting a coping strategy that led to the use rather than the suppression of emotions. The use of emotions provided workers with job satisfaction and greater control over service interactions. Management subsequently commandeered the use of emotions to complement the introduction of private sector management techniques and service delivery reforms, regaining control over worker-client interactions.
