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US 2013/0094701 A1Published application
Adaptive cross partition for learning weak classifiers
AssigneeNEC Laboratories America, Inc.
InventorChang Huang
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Abstract
Systems and methods are disclosed to perform object detection for images from an image sensor by reusing a 1-dimensional feature from a previously learned weak classifier and selecting a new feature to construct a 2-dimensional feature space; and cross partitioning the 2-dimensional space to learn optimal outputs for instances in each domain within a boosting framework.
Claims20
A process to perform object detection for images from
- an image sensor, comprising:
- reusing a 1-dimensional feature from a previously learned weak classifier and selecting a new feature to construct a 2-dimensional feature space;
- and
- cross partitioning the 2-dimensional space to learn optimal outputs for instances in each domain within a boosting framework.
1 more element
A system to perform object detection for images from an image sensor, comprising:
- means for reusing a 1-dimensional feature from a previously learned weak classifier and selecting a new feature to construct a 2-dimensional feature space;
- means for cross partitioning the 2-dimensional space to obtain a number of small block-wise regions with uneven width or height and approximately uniform distribution of training samples;
- means for aggregating the small block-wise regions into larger ones across both dimensions with discriminability;
- and
- means for learning optimal outputs for instances in each block-wise area independently for a boosting operation.
2 more elements
Dependencies are inferred from the claim text.