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Chapter and Conference Paper
Robust Multiple-People Tracking Using Colour-Based Particle Filters
Robust and accurate people tracking is a key task in many promising computer-vision applications. One must deal with non-rigid targets in open-world scenarios, whose shape and appearance evolve over time. Targ...
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Chapter and Conference Paper
On Reasoning over Tracking Events
High-level understanding of motion events is a critical task in any system which aims to analyse dynamic human-populated scenes. However, current tracking techniques still do not address complex interaction ev...
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Chapter
Beyond the Static Camera: Issues and Trends in Active Vision
Maximizing both the area coverage and the resolution per target is highly desirable in many applications of computer vision. However, with a limited number of cameras viewing a scene, the two objectives are co...
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Chapter
Robot Interactive Learning through Human Assistance
This chapter presents some real-life examples using the interactive multimodal framework; in this work, the robot is capable of learning through human assistance. The basic idea is to use the human feedback to...
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Chapter
Moving Cast Shadows Detection Methods for Video Surveillance Applications
Moving cast shadows are a major concern in today’s performance from broad range of many vision-based surveillance applications because they highly difficult the object classification task. Several shadow detec...
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Chapter and Conference Paper
Facial Age Estimation Through the Fusion of Texture and Local Appearance Descriptors
Automatic extraction of soft biometric characteristics from face images is a very prolific field of research. Among these soft biometrics, age estimation can be very useful for several applications, such as ad...
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Chapter and Conference Paper
A Comparative Evaluation of Regression Learning Algorithms for Facial Age Estimation
The problem of automatic age estimation from facial images poses a great number of challenges: uncontrollable environment, insufficient and incomplete training data, strong person-specificity, and high within-...
