http://cvssp-data.eps.surrey.ac.uk/Personal/AdrianHilton/Publications_files/survey_techrep.pdf

A survey of advances in vision-based human motion capture and analysis

https://escholarship.org/content/qt8755h7rn/qt8755h7rn.pdf?t=p0jvvs

Occupant behavior modeling for building performance simulation: Current state and future challenges:

Digital video imaging systems and techniques for efficiently transforming warped video images into rectilinear video images, real-time tracking of persons and objects, face recognition of persons, monitoring and tracking head pose of a person and associated perspective view of the person.

Digital processing of video images

Ambient intelligence (AmI) is a new multidisciplinary paradigm rooted in the ideas of NormanAuthor of the Invisible Computer [32]. and Ubiquitous Computing. AmI fosters novel anthropomorphic human–machine models of interaction. In AmI, technologies are deployed to make computers disappear in the background, while the human user moves into the foreground in complete control of the augmented environment. AmI is a user-centric paradigm, it supports a variety of artificial intelligence methods and works pervasively, nonintrusively, and transparently to aid the user. AmI supports and promotes interdisciplinary research encompassing the technological, scientific and artistic fields creating a virtual support for embedded and distributed intelligence.

/pdf/ambient-intelligence-a-new-multidisciplinary-paradigm-4hr88www1k.pdf

Ambient Intelligence: A New Multidisciplinary Paradigm

Intelligent environments can be viewed as systems where humans and machines (rooms) collaborate. Intelligent (or smart) environments need to extract and maintain an awareness of a wide range of events and human activities occurring in these spaces. This requirement is crucial for supporting efficient and effective interactions among humans as well as humans and intelligent spaces. Visual information plays an important role for developing accurate and useful representation of the static and dynamic states of an intelligent environment. Accurate and efficient capture, analysis, and summarization of the dynamic context requires the vision system to work at multiple levels of semantic abstractions in a robust manner. In this paper, we present details of a long-term and ongoing research project, where indoor intelligent spaces endowed with a range of useful functionalities are designed, built, and systematically evaluated. Some of the key functionalities include: intruder detection; multiple person tracking; body pose and posture analysis; person identification; human body modeling and movement analysis; and for integrated systems for intelligent meeting rooms, teleconferencing, or performance spaces. The paper includes an overall system architecture to support design and development of intelligent environments. Details of panoramic (omnidirectional) video camera arrays, calibration, video stream synchronization, and real-time capture/processing are discussed. Modules for multicamera-based multiperson tracking, event detection and event based servoing for selective attention, voxelization, streaming face recognition, are also discussed. The paper includes experimental studies to systematically evaluate performance of individual video analysis modules as well as to evaluate basic feasibility of an integrated system for dynamic context capture and event based servoing, and semantic information summarization.

/pdf/dynamic-context-capture-and-distributed-video-arrays-for-4m12hpz27g.pdf

Dynamic context capture and distributed video arrays for intelligent spaces

Intelligent environments provide challenging research problems for natural and efficient interfaces between humans and computers as well as between humans. We present a multimodal sensory intelligent system testbed based on some general requirements for developing intelligent environments. We also present rigorous experimental investigations on the processing and control modules for the active camera networks and the microphone array which are embedded in the intelligent room. An integrated intelligent system is developed utilizing four basic modules for visual and audio processing. The integrated system has the functionality of human tracking, active camera control, face recognition and speaker recognition. This system is demonstrated to be suitable for teleconferencing type of applications.

Huang Kohsia

Papers

Intelligent environments and active camera networks