First published 10/2/2026, 7:53:15 PM · Last updated 10/2/2026, 7:53:15 PM

Object tracking using an adaptive Kalman filter combined with mean shift

Journal article describing a method that combines an adaptive Kalman filter with mean-shift for object tracking. Source metadata indicate a journal publication but provide no further event details.

Illustrative image: KENNEDY SPACE CENTER, FLA. - A worker calibrates a tracking telescope, part of the Distant Object Attitude Measurement System (DOAMS), located in Cocoa Beach, Fla. The telescope provides optical support for launches from KSC and Cape Canaveral. — NASA/KSC/NASA Image and Video Library, NASA Media Usage Guidelines

Categories: science-and-space, technology

Generated scores

Scores are based on the cited reporting and use a 1–10 scale. Read the methodology.

Confidence: 5/10How certain the assessment is based on the clarity and evidence in the cited reporting.
Geographic reach: 1/10How widely the event reaches, from a local area (1) to worldwide impact (10).
Global importance: 3/10The event's broader significance, from limited importance (1) to major global importance (10).
Impact magnitude: 3/10The scale or severity of the real-world impact, from minor (1) to extreme (10).
Positivity: 5/10How harmful or beneficial the event is, from strongly harmful (1) to strongly positive (10).
Urgency: 1/10How time-sensitive the event is, from low urgency (1) to immediate attention needed (10).

Why it matters

Relevant to researchers and students working on computer vision and tracking algorithms.

Sources

Object tracking using an adaptive Kalman filter combined with mean shift

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