Using Covariance Matrices as Feature Descriptors for Vehicle Detection from a Fixed Camera

Computer Science – Computer Vision and Pattern Recognition

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Written as part of the requirements for the SC/EC520 course in Digital Image Processing at Boston University

Scientific paper

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.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Using Covariance Matrices as Feature Descriptors for Vehicle Detection from a Fixed Camera does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Using Covariance Matrices as Feature Descriptors for Vehicle Detection from a Fixed Camera, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Using Covariance Matrices as Feature Descriptors for Vehicle Detection from a Fixed Camera will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-371582

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.