Leveraging Structural Context Models and Ranking Score Fusion for Human Interaction Prediction
MetadataShow full item record
© 1999-2012 IEEE. Predicting an interaction before it is fully executed is very important in applications, such as human-robot interaction and video surveillance. In a two-human interaction scenario, there are often contextual dependency structures between the global interaction context of the two humans and the local context of the different body parts of each human. In this paper, we propose to learn the structure of the interaction contexts and combine it with the spatial and temporal information of a video sequence to better predict the interaction class. The structural models, including the spatial and the temporal models, are learned with long short term memory (LSTM) networks to capture the dependency of the global and local contexts of each RGB frame and each optical flow image, respectively. LSTM networks are also capable of detecting the key information from global and local interaction contexts. Moreover, to effectively combine the structural models with the spatial and temporal models for interaction prediction, a ranking score fusion method is introduced to automatically compute the optimal weight of each model for score fusion. Experimental results on the BIT-Interaction Dataset and the UT-Interaction Dataset clearly demonstrate the benefits of the proposed method.
Showing items related by title, author, creator and subject.
Nie, Katherine Su (2007)Numerous popular business publications and academic literature have highlighted that the Chinese cultural phenomenon of guanxi has made noticeable impacts on the economic efficiency in China’s economic transition. Despite ...
Modelling the co-occurence of Streptococcus pneumoniae with other bacterial and viral pathogens in the upper respiratory tractJacoby, P.; Watson, K.; Bowman, J.; Taylor, A.; Riley, T.; Smith, D.; Lehmann, Deborah (2007)Go to ScienceDirect® Home Skip Main Navigation Links Brought to you by: The University of Western Australia Library Login: + Register Athens/Institution Login Not Registered? - User Name: Password: ...
Trust and reputation for service-oriented environments: Technologies for building business intelligence and consumer confidenceChang, Elizabeth; Dillon, Tharam S.; Hussain, Farookh (2006)Trust has played a central role in human relationships and hence has been the subject of study in many fields including business, law, social science, philosophy and psychology. It has played a pivotal role in forming ...