Stationary target detection by exploiting changes in background model
AssigneeObjectVideo, Inc.
InventorsKhurram Hassan-Shafique, Péter L. Venetianer, Li Yu, Haiying Liu
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Abstract
A computer-implemented method for processing one or more video frames may include obtaining one or more video frames; generating one or more blobs using the one or more video frames; classifying the one or more blobs to produce one or more classified blobs, wherein the one or more classified blobs include one or more of a stationary target, a moving target, a target insertion, a target removal, or a local change; and constructing a list of detected targets based on the one or more classified blobs.
Claims19
A computer-implemented method for processing one or more video frames, comprising:
- obtaining, by a computer, one or more video frames;
- generating, by the computer, one or more blobs using the one or more video frames;
- classifying, by the computer, the one or more blobs to produce one or more classified blobs, wherein the one or more classified blobs include one or more of a stationary target, a moving target, a target insertion, a target removal, or a local change;
- and
- constructing a list of detected targets based on the one or more classified blobs.
A system for processing one or more video frames, the system comprising:
- a computer adapted to obtain one or more video frames, wherein the computer is adapted to:
- generate one or more blobs using the one or more video frames;
- classify the one or more blobs to produce one or more classified blobs, wherein the one or more classified blobs include one or more of a stationary target, a moving target, a target insertion, a target removal, or a local change;
- and
- construct a list of detected targets based on the one or more classified blobs.
A system for processing one or more video frames, the system comprising:
- a computer adapted to obtain one or more video frames, wherein the computer is adapted to:
- generate a first background model using the one or more video frames;
- generate a second background model using the one or more video frames;
- compare the first background model and the second background model to generate a comparison;
- and
- generate one or more blobs in response to the comparison.
Dependencies are inferred from the claim text.