Difference between revisions of "User:Xinkeqiong"
Xinkeqiong (talk | contribs) (→How to use OpenCV to train Classifiers for image detection) |
m (Moved to ECE597Spring2010) |
||
| (4 intermediate revisions by one other user not shown) | |||
| Line 1: | Line 1: | ||
| + | [[Category:ECE597Spring2010 |U]] | ||
| + | |||
Hi, My name is Keqiong "Claire" Xin. I'm now pursuing the Master Degree of Computer Engineering in Rose-Hulman. This is my user page for course ECE597 Embedded Linux. | Hi, My name is Keqiong "Claire" Xin. I'm now pursuing the Master Degree of Computer Engineering in Rose-Hulman. This is my user page for course ECE597 Embedded Linux. | ||
| + | |||
| + | == Our Project == | ||
| + | Our project in this course is [[ECE597: Auto HUD]]. All the documentation is contained in the page link. | ||
| + | |||
| + | The idea of this project is to recognize road signs with Beagleboard and camera, and display the result through the pico projector. | ||
| + | |||
| + | 1. Build the sample set for training, and using Haar training program to train the samples. | ||
| + | |||
| + | 2. Working on sign detection code to optimize the detection result. | ||
| + | |||
| + | 3. Get the display buffer working. | ||
== Chapter 2 == | == Chapter 2 == | ||
| Line 24: | Line 37: | ||
* [[ECE597 Listings for Chapter 8 xink | Listings for Chapter 8 ]] | * [[ECE597 Listings for Chapter 8 xink | Listings for Chapter 8 ]] | ||
| − | |||
| − | |||
| − | |||
| − | |||
Latest revision as of 17:10, 21 July 2014
Hi, My name is Keqiong "Claire" Xin. I'm now pursuing the Master Degree of Computer Engineering in Rose-Hulman. This is my user page for course ECE597 Embedded Linux.
Our Project
Our project in this course is ECE597: Auto HUD. All the documentation is contained in the page link.
The idea of this project is to recognize road signs with Beagleboard and camera, and display the result through the pico projector.
1. Build the sample set for training, and using Haar training program to train the samples.
2. Working on sign detection code to optimize the detection result.
3. Get the display buffer working.
