Techniques of vision-based motion analysis aim to detect track identify and generally
understand the behavior of objects in image sequences. With the growth of video data in a wide
range of applications from visual surveillance to human-machine interfaces the ability to
automatically analyze and understand object motions from video footage is of increasing
importance. Among the latest developments in this field is the application of statistical
machine learning algorithms for object tracking activity modeling and recognition. Developed
from expert contributions to the first and second International Workshop on Machine Learning
for Vision-Based Motion Analysis this important text reference highlights the latest
algorithms and systems for robust and effective vision-based motion understanding from a
machine learning perspective. Highlighting the benefits of collaboration between the
communities of object motion understanding and machine learning the book discusses the most
active forefronts of research including current challenges and potential future directions.
Topics and features: provides a comprehensive review of the latest developments in vision-based
motion analysis presenting numerous case studies on state-of-the-art learning algorithms
examines algorithms for clustering and segmentation and manifold learning for dynamical models
describes the theory behind mixed-state statistical models with a focus on mixed-state Markov
models that take into account spatial and temporal interaction discusses object tracking in
surveillance image streams discriminative multiple target tracking and guidewire tracking in
fluoroscopy explores issues of modeling for saliency detection human gait modeling modeling
of extremely crowded scenes and behavior modeling from video surveillance data investigates
methods for automatic recognition of gestures in Sign Language and human action recognition
from small training sets. Researchers professional engineers and graduate students in
computer vision pattern recognition and machine learning will all find this text an
accessible survey of machine learning techniques for vision-based motion analysis. The book
will also be of interest to all who work with specific vision applications such as
surveillance sport event analysis healthcare video conferencing and motion video indexing
and retrieval.
