Using Covariance Matrices as Feature Descriptors for Vehicle Detection from a Fixed Camera
Seminar paper from the year 2006 in the subject Computer Science - Applied, grade: A, Boston University, course: Digital Image Processing and Communication, language: English, abstract: A method is developed to distinguish between cars and trucks present in a video feed of a highway. The method builds upon previously done work using covariance matrices
as an accurate descriptor for regions. Background subtraction and other similar proven image processing techniques are used to identify the regions where the vehicles are most likely to be, and a distance metric comparing the vehicle inside the region to a fixed library of vehicles is used to determine the class of vehicle.
1119551694
Using Covariance Matrices as Feature Descriptors for Vehicle Detection from a Fixed Camera
Seminar paper from the year 2006 in the subject Computer Science - Applied, grade: A, Boston University, course: Digital Image Processing and Communication, language: English, abstract: A method is developed to distinguish between cars and trucks present in a video feed of a highway. The method builds upon previously done work using covariance matrices
as an accurate descriptor for regions. Background subtraction and other similar proven image processing techniques are used to identify the regions where the vehicles are most likely to be, and a distance metric comparing the vehicle inside the region to a fixed library of vehicles is used to determine the class of vehicle.
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Using Covariance Matrices as Feature Descriptors for Vehicle Detection from a Fixed Camera
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Using Covariance Matrices as Feature Descriptors for Vehicle Detection from a Fixed Camera
13
17.95
In Stock
Product Details
| ISBN-13: | 9783638849722 |
|---|---|
| Publisher: | GRIN Verlag GmbH |
| Publication date: | 01/01/2007 |
| Sold by: | CIANDO |
| Format: | eBook |
| Pages: | 13 |
| File size: | 2 MB |
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