A camera-based system for tracking people in real time

  • Segen J
  • Pingali S
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This paper describes a system for real-time tracking of people in
video sequences. The input to the system is live or recorded video data
acquired by a stationary camera in an environment where the primary
moving objects are people. The output consists of trajectories which
give the spatio-temporal coordinates of individual persons as they move
in the environment. The system uses a new model-based approach to object
tracking. It identifies feature points in each video frame, matches
feature points across frames to produce feature “paths”,
then groups short-lived and partially overlapping feature paths into
longer living trajectories representing motion of individual persons.
The path grouping is based on a novel model-based algorithm for motion
clustering. The system runs on an SGI Indy workstation at an average
rate of 14 frames a second. The system has numerous applications since
various statistics and indicators of human activity can be derived from
the motion trajectories. Examples of these indicators described in the
paper include people counts, presence and time spent in a region,
traffic density maps and directional traffic statistics

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  • Jakub Segen

  • Sarma Pingali

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