Vehware Project ---: Difference between revisions
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-Human body has a specific shape and can be easily distinguished among other object by its gradient properties. But in order to do that developer needs a pre-trained HOG features. |
-Human body has a specific shape and can be easily distinguished among other object by its gradient properties. But in order to do that developer needs a pre-trained HOG features. |
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[[File:2016-02-07 22 16 07-people detector.png]] |
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This photo is the output of the built-in HOG function of OpenCV. While It seems that method gives accurate results, the amount of time that the method spends is too much for a picture. It needs to be reduced. |
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Revision as of 15:49, 8 February 2016
01/31/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc... .
-Discussed the CPT process and printed the forms.
- Attachments A and B are updated for CPT forms
- CPT forms are prepared
- Previous Senior Project codes are prepared to send to Merwyn Jones
-Spoke with Mr. Bill on semester project and he identified a few to-dos to optimize the existing code,also talked about achievements done so far and technologies that are already launched public to get information to lead our ways.
-Decided the future goals talked about algorithms to use and discussed the pros and cons of them. Also the team wants Mr Bill to find help with asking questions about our problems about our code and algorithms.
- Detailed new Gantt chart going to be ready and going to be uploaded here based on selected human and car detection algorithms
-For the this semester we are going to deliver the plan items via the Gantt chart and we will end up with a program that does:
1 Auto detection of cars
2 Notification to driver
3 Danger zones
4 Human detection and Tracking
5 Reduce false alarms
- As a team we make task sharing and start to work on our own goals (like detailed gantt chart, finding and trying human detection algorithms, pedestrian detection with machine learning)
Huseyin is assigned to research the vehicle detection by plates
Ahmet : research pedestrian detection using hog, and application of machine learning for object detection
Okan: study example code of a autonomus RC car
02/07/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
-Ganttchart will be updated upon the decision made on meeting with Mr. Bill
-CPT forms were signed and handed in to Watson office.
-During that time team members did their independent researches
-Histogram oriented gradients method is studied.
-Histogram oriented gradients (HOG) aimed to used to find "gradient" of a pixel. What the gradient information contains whether the pixel is on an edge line, direction of this edge, and how strong is this edge (src)
-Human body has a specific shape and can be easily distinguished among other object by its gradient properties. But in order to do that developer needs a pre-trained HOG features.
This photo is the output of the built-in HOG function of OpenCV. While It seems that method gives accurate results, the amount of time that the method spends is too much for a picture. It needs to be reduced.
-Detecting cars based on their general properties might be good idea for automatic detection because of that focused on plate recognition
-Cars has certain shape of plates only difference between them is their colors
-Detecting vehicles by plates could decrease calculation and make algorithm faster
-Bad side of the plate based recognition of the car is when an out ridden car might be out of range in small distance when we compare with the holistic detection of the car
-Started to search on Aforge.net library which include faster algorithm on shape recognition.
-Encountered with significatant level of false alarms
02/14/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
02/21/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
02/28/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
03/06/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
03/13/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
03/20/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
03/27/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
04/03/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
04/10/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
04/17/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
04/24/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
05/01/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
05/08/2016 Weekly activities including accomplishments, problems changes to plan, meeting minutes, etc...
