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17
Audio-visual multi-person tracking and identification for smart environments
- In Proceedings of the 15th international Conference on Multimedia (Augsburg, Germany). MULTIMEDIA '07. ACM
, 2007
"... This paper presents a novel system for the automatic and unobtrusive tracking and identification of multiple persons in an indoor environment. Information from several fixed cameras is fused in a particle filter framework to simultaneously track multiple occupants. A set of steerable fuzzycontrolled ..."
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Cited by 22 (1 self)
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This paper presents a novel system for the automatic and unobtrusive tracking and identification of multiple persons in an indoor environment. Information from several fixed cameras is fused in a particle filter framework to simultaneously track multiple occupants. A set of steerable fuzzycontrolled pan-tilt-zoom cameras serves to smoothly track persons of interest and opportunistically capture facial closeups for face identification. In parallel, speech segmentation, sound source localization and speaker identification are performed using several far-field microphones and arrays. The information coming asynchronously and sporadically from several sources, such as track updates and spatio-temporally localized visual and acoustic identification cues, is fused at higher level to gradually refine the global scene model and increase the system’s confidence in the set of recognized identities. The system has been trained on a small set of users ’ faces and/or voices and showed good performance in natural meeting scenarios at quickly acquiring their identities and complementing the ID information missing in single modalities.
Tracking People with Networks of Heterogeneous Sensors
- IN PROCEEDINGS OF THE AUSTRALASIAN CONFERENCE ON ROBOTICS AND AUTOMATION
, 2004
"... This paper describes the theory and implementation of a system of distributed sensors which work together to identify and track moving people using di#erent sensing modalities in real time. Algorithms for detecting people using cameras and laser scanners are presented. A Kalman ..."
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Cited by 11 (0 self)
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This paper describes the theory and implementation of a system of distributed sensors which work together to identify and track moving people using di#erent sensing modalities in real time. Algorithms for detecting people using cameras and laser scanners are presented. A Kalman
A Self-Referential Perceptual Inference Framework for Video Interpretation
- In Proceedings of the International Conference on Vision Systems
, 2003
"... This paper presents an extensible architectural model for general content-based analysis and indexing of video data which can be customised for a given problem domain. Video interpretation is approached as a joint inference problem which can be solved through the use of modern machine learning and p ..."
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Cited by 9 (0 self)
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This paper presents an extensible architectural model for general content-based analysis and indexing of video data which can be customised for a given problem domain. Video interpretation is approached as a joint inference problem which can be solved through the use of modern machine learning and probabilistic inference techniques. An important aspect of the work concerns the use of a novel active knowledge representation methodology based on an ontological query language. This representation allows one to pose the problem of video analysis in terms of queries expressed in a visual language incorporating prior hierarchical knowledge of the syntactic and semantic structure of entities, relationships, and events of interest occurring in a video sequence. Perceptual inference then takes place within an ontological domain defined by the structure of the problem and the current goal set.
Auditory Evidence Grids
- Proceedings of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS
, 2006
"... Abstract – Sound source localization on a mobile robot can be a difficult task due to a variety of problems inherent to a real environment, including robot ego-noise, echoes, and the transient nature of ambient noise. As a result, source localization data are often very noisy and unreliable. In this ..."
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Cited by 7 (1 self)
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Abstract – Sound source localization on a mobile robot can be a difficult task due to a variety of problems inherent to a real environment, including robot ego-noise, echoes, and the transient nature of ambient noise. As a result, source localization data are often very noisy and unreliable. In this work, we overcome some of these problems by combining the localization evidence over a variety of robot poses using an evidence grid. The result is a representation that localizes the pertinent objects well over time, can be used to filter poor localization results, and may also be useful for global re-localization from sound localization results.
Integration of angle of arrival information for multimodal sensor network localization using semidefinite programming
- In Proceedings of 39th Asilomar Conference on Signals, Systems and Computers
, 2005
"... The problem of position estimation in sensor networks using a combination of distance and angle information as well as pure angle information is discussed. For this purpose, a semidefinite programming relaxation based method that has been demonstrated on pure distance information is extended to solv ..."
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Cited by 6 (0 self)
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The problem of position estimation in sensor networks using a combination of distance and angle information as well as pure angle information is discussed. For this purpose, a semidefinite programming relaxation based method that has been demonstrated on pure distance information is extended to solve the problem. Practical considerations such as the effect of noise and computational effort are also addressed. In particular, a random constraint selection method to minimize the number of constraints in the problem formulation is described. The performance evaluation of the technique with regard to estimation accuracy and computation time is also presented by the means of extensive simulations.
Performance analysis for automated gait extraction and recofnition . . .
- MULTIMED TOOLS APPL
, 2009
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Combining Environmental Cues & Head Gestures to Interact with Wearable Devices
- in Proc. Int. Conf. on Multimodal Interfaces, 2005
"... As wearable sensors and computing hardware are becoming a reality, new and unorthodox approaches to seamless human-computer interaction can be explored. This paper presents the prototype of a wearable, head-mounted device for advanced human-machine interaction that integrates speech recognition and ..."
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Cited by 4 (2 self)
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As wearable sensors and computing hardware are becoming a reality, new and unorthodox approaches to seamless human-computer interaction can be explored. This paper presents the prototype of a wearable, head-mounted device for advanced human-machine interaction that integrates speech recognition and computer vision with head gesture analysis based on inertial sensor data. We will focus on the innovative idea of integrating visual and inertial data processing for interaction. Fusing head gestures with results from visual analysis of the environment provides rich vocabularies for human-machine communication because it renders the environment into an interface: if objects or items in the surroundings are being associated with system activities, head gestures can trigger commands if the corresponding object is being looked at. We will explain the algorithmic approaches applied in our prototype and present experiments that highlight its potential for assistive technology. Apart from pointing out a new direction for seamless interaction in general, our approach provides a new and easy to use interface for disabled and paralyzed users in particular.
Multi-sensory and multi-modal fusion for sentient computing
- Int. J. Comput. Vis
, 2007
"... Abstract. This paper presents an approach to multi-sensory and multi-modal fusion in which computer vision information obtained from calibrated cameras is integrated with a large-scale sentient computing system known as “SPIRIT”. The SPIRIT system employs an ultrasonic location infrastructure to tra ..."
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Cited by 4 (1 self)
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Abstract. This paper presents an approach to multi-sensory and multi-modal fusion in which computer vision information obtained from calibrated cameras is integrated with a large-scale sentient computing system known as “SPIRIT”. The SPIRIT system employs an ultrasonic location infrastructure to track people and devices in an office building and model their state. Vision techniques include background and object appearance modelling, face detection, segmentation, and tracking modules. Integration is achieved at the system level through the metaphor of shared perceptions, in the sense that the different modalities are guided by and provide updates to a shared world model. This model incorporates aspects of both the static (e.g. positions of office walls and doors) and the dynamic (e.g. location and appearance of devices and people) environment. Fusion and inference are performed by Bayesian networks that model the probabilistic dependencies and reli-abilities of different sources of information over time. It is shown that the fusion process significantly enhances the capabilities and robustness of both sensory modalities, thus enabling the system to maintain a richer and more accurate world model.
Probabilistic Integration of Sparse Audio-Visual Cues for Identity Tracking
- Proceeding of the ACM International Conference on Multimedia
, 2008
"... In the context of smart environments, the ability to track and identify persons is a key factor, determining the scope and flexibility of analytical components or intelligent services that can be provided. While some amount of work has been done concerning the camera-based tracking of multiple users ..."
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Cited by 4 (1 self)
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In the context of smart environments, the ability to track and identify persons is a key factor, determining the scope and flexibility of analytical components or intelligent services that can be provided. While some amount of work has been done concerning the camera-based tracking of multiple users in a variety of scenarios, technologies for acoustic and visual identification, such as face or voice ID, are unfortunately still subjected to severe limitations when distantly placed sensors have to be used. Because of this, reliable cues for identification can be hard to obtain without user cooperation, especially when multiple users are involved. In this paper, we present a novel technique for the tracking and identification of multiple persons in a smart environment using distantly placed audio-visual sensors. The technique builds on the opportunistic integration of tracking as well as face and voice identification cues, gained from several cameras and microphones, whenever these cues can be captured with a sufficient degree of confidence. A probabilistic model is used to keep track of identified persons and update the belief in their identities whenever new observations can be made. The technique has been systematically evaluated on the CLEAR Interactive Seminar database, a large audio-visual corpus of realistic meeting scenarios captured in a variety of smart rooms.
A Review of Decision Support Systems in Telecare
"... This paper presents an overview of the state-of-the-art on decision support systems (DSS) in telecare. The main aspect examined is the use of smaller subsystems— components in an integrated DSS, with emphasis on two application areas: medical home unit monitoring and real-time prioritisation of the ..."
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Cited by 2 (0 self)
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This paper presents an overview of the state-of-the-art on decision support systems (DSS) in telecare. The main aspect examined is the use of smaller subsystems— components in an integrated DSS, with emphasis on two application areas: medical home unit monitoring and real-time prioritisation of the alerts generated by them, and drug interaction checking. The paper suggests the development of an integrated hybrid telecare DSS synthesizing most of the technologies reviewed. Implementation issues are also examined, with an emphasis on the international trend towards the development of platform-independent, component-based, distributed software. KEY WORDS: telecare; decision support systems; alert prioritisation.
