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Space plays a fundamental role in human cognition. In everyday situations, it is often viewed as a construct induced by spatial relationships, rather than as a container that exists independently of the objects located in it. Spatial relationships, therefore, have been thoroughly investigated in many disciplines, including cognitive science, psychology, linguistics, geography and artificial intelligence...
A reliable model-based human motion tracking scheme is presented. In this approach, silhouette image sequences from a top-view camera and a side-view camera work together to track human motion in 3D space in real time. The adoption of one top view camera introduces many attractive characteristics. A convenient calibration scheme is presented by decoupling different camera parameters to the largest...
This paper presents a novel method for learning classes of temporal sequences using a bag-of-features approach. We define a temporal sequence as a bag of temporal features and show how this representation can be used for the recognition and segmentation of temporal events. A codebook of temporal descriptors, representing the local temporal texture, is automatically constructed from a set of sample...
Particle filtering (also known as the condensation algorithm) has been widely applied to model-based human motion capture. However, the number of particles required for the algorithm to work increases exponentially with the dimensionality of the model. In order to alleviate this computational explosion, we propose a two-level hierarchical framework. At the coarse level, the configuration space is...
We developed a novel markerless motion capture system and explored its use in documenting elder exercise routines in a health club. This system uses image contour tracking and swarm intelligence methods to track the location of the spine and shoulders during three exercises - treadmill, exercise bike, and overhead lateral pull-down. Preliminary results of our qualitative study demonstrate that our...
Linguistic tagging of images require proper detection of language concepts from pictures, which is a challenging issue. Preparation of representative samples to demonstrate concepts is the first step; learning parameters from those training samples and setting up a classifier is the next step; proper tag set definition, extraction of relative contextual concepts, filtering and inference drawing for...
Large-scale video surveillance systems typically deploy many video cameras over a wide area and display video streams on separate screens. Operators of this kind of systems have difficulties perceiving the whole pictures of intermixed views and are prone to losing track of targets. This paper presents a surveillance system which integrates videos from multiple cameras into a single comprehensive view...
A large volume of visual content is inaccessible until effective and efficient indexing and retrieval of such data is achieved. In this paper, we introduce the dream system, which is a knowledge-assisted semantic-driven context-aware visual information retrieval system applied in the film post production domain. We mainly focus on the automatic labelling and topic map related aspects of the framework...
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