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Social Signal Processing: State-of-the-art and future perspectives of an emerging domain
- IN PROCEEDINGS OF THE ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA
, 2008
"... The ability to understand and manage social signals of a person we are communicating with is the core of social intelligence. Social intelligence is a facet of human intelligence that has been argued to be indispensable and perhaps the most important for success in life. This paper argues that next- ..."
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Cited by 27 (7 self)
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The ability to understand and manage social signals of a person we are communicating with is the core of social intelligence. Social intelligence is a facet of human intelligence that has been argued to be indispensable and perhaps the most important for success in life. This paper argues that next-generation computing needs to include the essence of social intelligence – the ability to recognize human social signals and social behaviours like politeness, and disagreement – in order to become more effective and more efficient. Although each one of us understands the importance of social signals in everyday life situations, and in spite of recent advances in machine analysis of relevant behavioural cues like blinks, smiles, crossed arms, laughter, and similar, design and development of automated systems for Social Signal Processing (SSP) are rather difficult. This paper surveys the past efforts in solving these problems by a computer, it summarizes the relevant findings in social psychology, and it proposes aset of recommendations for enabling the development of the next generation of socially-aware computing.
Robust, low-cost, non-intrusive sensing and recognition of seated postures
- In Proc. UIST
, 2007
"... ABSTRACT In this paper, we present a methodology for recognizing seated postures using data from pressure sensors installed on a chair. Information about seated postures could be used to help avoid adverse effects of sitting for long periods of time or to predict seated activities for a human-compu ..."
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ABSTRACT In this paper, we present a methodology for recognizing seated postures using data from pressure sensors installed on a chair. Information about seated postures could be used to help avoid adverse effects of sitting for long periods of time or to predict seated activities for a human-computer interface. Our system design displays accurate near-real-time classification performance on data from subjects on which the posture recognition system was not trained by using a set of carefully designed, subject-invariant signal features. By using a near-optimal sensor placement strategy, we keep the number of required sensors low thereby reducing cost and computational complexity. We evaluated the performance of our technology using a series of empirical methods including (1) cross-validation (classification accuracy of 87% for ten postures using data from 31 sensors), and (2) a physical deployment of our system (78% classification accuracy using data from 19 sensors).
Context-Aware 3D Gesture Interaction Based on Multiple Kinects
"... Abstract—This paper presents a novel context-aware system for deictic gestures interaction with smart environments. The system tracks multiple users; moreover, it recognizes inhabitants ’ postures and gestures in real-time. This information, enriched with smart objects coordinates, is reconstructed ..."
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Abstract—This paper presents a novel context-aware system for deictic gestures interaction with smart environments. The system tracks multiple users; moreover, it recognizes inhabitants ’ postures and gestures in real-time. This information, enriched with smart objects coordinates, is reconstructed in a 3D model to allow the recognition process. Finally the system executes the programmed tasks to support the users ’ activity. Two Microsoft Kinect depth cameras have been used to acquire the data and a framework for the communication with the smart objects has been adopted. A first prototype has been developed and an evaluation test with 13 users has been conducted in order to assess the usability of the system. Results show that this interaction experience has been really appreciated by the users.
FLEXIBLE 3D OBJECT RECOGNITION FRAMEWORK USING 2D VIEWS VIA A SIMILARITY-BASED ASPECT-GRAPH APPROACH
, 2008
"... This work presents a flexible framework for recognizing 3D objects from 2D views. Similarity-based aspect-graph, which contains a set of aspects and prototypes for these aspects, is employed to represent the database of 3D objects. An incremental database construction method that maximizes the simil ..."
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This work presents a flexible framework for recognizing 3D objects from 2D views. Similarity-based aspect-graph, which contains a set of aspects and prototypes for these aspects, is employed to represent the database of 3D objects. An incremental database construction method that maximizes the similarity of views in the same aspect and minimizes the similarity of prototypes is proposed as the core of the framework to build and update the aspect-graph using 2D views randomly sampled from a viewing sphere. The proposed framework is evaluated on various object recognition problems, including 3D object recognition, human posture recognition and scene recognition. Shape and color features are employed in different applications with the proposed framework and the top three matching rates show the efficiency of the proposed method.
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, 2008
"... Human activity recognition using limb component extraction ..."
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