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Detecting and Analyzing Multiple Moving Objects in a Crowd

Oak Ridge National Laboratory

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PDF Document Publication11-G00265_ID2135.pdf (621 KB)

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<p><span style="font-size: xx-small;">Sample multi-object detection results from the algorithm: The red number indicates the aggregate count of independently moving objects detected.</span></p>


Sample multi-object detection results from the algorithm: The red number indicates the aggregate count of independently moving objects detected.

Technology Marketing SummaryWhile human eyes can unconsciously perceive independent objects in coherent motion patterns such as crowds, automated systems have difficulty detecting and counting independently moving objects. A robust algorithm that works with a video recording apparatus to detect, count, and analyze regions of activity in crowds was developed by computer scientists at ORNL. The algorithm selects regions of coherent motion in both time and space, and then identifies sets of tracks that may contain objects of interest.DescriptionThe technology includes an apparatus for identifying a moving object within a series of video images, an image recording device that stores images in a time series, and an image analysis feature configured to execute a program of instructions to identify the object. The program’s steps include identifying several feature point tracks in which all feature points belonging to the same track are located within a polygon of predefined size. It then calculates a trajectory similarity factor where each similarity is a measure of a maximum distance between two tracks.Benefits•Can automatically locate and count objects in high-density crowds with accuracy
•Overcomes some of the difficulties in detecting individual objects that move in unison
•Requires no complex shape or appearance models to select objects
Applications and Industries• Detecting and counting any type of moving object
• Estimating crowd size for event management and planning
• Support for analyses requiring counts of moving objects, such as in medical analysis
• Security and surveillance
More InformationAnil M. Cheriyadat. Detecting Multiple Moving Objects in Crowded Environments with Coherent Motion Regions, U.S. Patent Application 12/489,589, filed June 23, 2009.Patents and Patent Applications
ID Number
Title and Abstract
Primary Lab
Patent 8,462,987
Detecting multiple moving objects in crowded environments with coherent motion regions
Coherent motion regions extend in time as well as space, enforcing consistency in detected objects over long time periods and making the algorithm robust to noisy or short point tracks. As a result of enforcing the constraint that selected coherent motion regions contain disjoint sets of tracks defined in a three-dimensional space including a time dimension. An algorithm operates directly on raw, unconditioned low-level feature point tracks, and minimizes a global measure of the coherent motion regions. At least one discrete moving object is identified in a time series of video images based on the trajectory similarity factors, which is a measure of a maximum distance between a pair of feature point tracks.
Oak Ridge National Laboratory 06/11/2013
Technology Status
Technology IDDevelopment StageAvailabilityPublishedLast Updated
UT-B ID 200802135DevelopmentAvailable11/21/201110/27/2011

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To: David L. Sims<>