Motion based segmentor for occupant tracking using a hausdorf distance heuristic
First Claim
1. A method for isolating a current segmented image from a current ambient image captured by a sensor, said image segmentation method comprising:
- comparing the current ambient image to a prior ambient image;
identifying a border of the current segmented image by differences between the current ambient image and the prior ambient image; and
matching a template to the identified border with a Hausdorf distance heuristic.
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Abstract
A segmentation system is disclosed that allows a segmented image of a vehicle occupant to be identified within an overall image (the “ambient image”) of the area that includes the image of the occupant. The segmented image from a past sensor measurement within can help determine a region of interest within the most recently captured ambient image. To further reduce processing time, the system can be configured to assume that the bottom of segmented image does not move. Differences between the various ambient images captured by the sensor can be used to identify movement by the occupant, and thus the boundary of the segmented image. A template image is then fitted to the boundary of the segmented image for an entire range of predetermined angles. The validity of each fit within the range of angles can be evaluated. The template image can also be modified for future ambient images.
46 Citations
31 Claims
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1. A method for isolating a current segmented image from a current ambient image captured by a sensor, said image segmentation method comprising:
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comparing the current ambient image to a prior ambient image;
identifying a border of the current segmented image by differences between the current ambient image and the prior ambient image; and
matching a template to the identified border with a Hausdorf distance heuristic. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
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26. A method for isolating a current segmented image from a current ambient image, comprising:
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identifying a region of interest in the current ambient image from a previous ambient image;
applying a low-pass filter to an image difference determined by comparing the region of interest in the current ambient image to a corresponding area in the previous ambient image;
performing an image gradient calculation for finding a region in the current ambient image with a rapidly changing image amplitude;
thresholding the image difference with a predetermined cumulative distribution function;
cleaning the results of the image gradient calculation;
matching a template image to the cleaned results with a Hausdorf distance heuristic; and
fitting an ellipse to the template image.
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27. A segmentation system for isolating a segmented image from an ambient image, comprising:
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an ambient image, including a segmented image and an area of interest;
a gradient image module, including a gradient image, wherein said gradient image module generates said gradient image in said area of interest; and
a template module, including a template, a template match, and a Hausdorf heuristic, wherein said template module generates said template match from said template, said gradient image, and said Hausdorf heuristic. - View Dependent Claims (28, 29, 31)
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30. The system of 29, further comprising a range of angles including a plurality of predefined angles, wherein said template module rotates said template in each of said plurality of predefined angles.
Specification