Revision history [back]

How come Surf Detector is better than Sift in my code

Hi Hi i'm evaluating SIFT and SURF Detectors in my project with mikolajczyk Dataset. you can find it here:http://www.robots.ox.ac.uk/~vgg/research/affine/

according to below papers SIFT should outperform SURF in scale, blur and rotation changes: "A performance evaluation of SIFT and SURF for multispectral image matching" "A Comparison of SIFT, PCA-SIFT and SURF" Same Dataset has been used. "SIFT and SURF Performance Evaluation Against Various Image Deformations on Benchmark Dataset"

i get below result for Bike (Blur) images

image description

i also used below codes for SIFT and SURF detector: (it's main code and not all of it) //Notice That SIFT and SURF code run separately and variables not getting overwrite.

SiftFeatureDetector detector;
detector.detect(img_1, key_points_1);
detector.detect(img_2, key_points_2);

int minHessian = 5000;             
SurfFeatureDetector detector(minHessian);   
detector.detect(img_1, key_points_1);
detector.detect(img_2, key_points_2);

cv::evaluateFeatureDetector(img_1c, img_2c, h12, &key_points_1, &key_points_2, repeatability, corrCounter); //H12 is homography matrix which was included in the Dataset

Did i miss something ? why my results is different?(also checked scale and rotation change and still SURF outperform SIFT)

How come Surf Detector is better than Sift in my code

Hi Hi i'm evaluating SIFT and SURF Detectors in my project with mikolajczyk Dataset. you can find it here:http://www.robots.ox.ac.uk/~vgg/research/affine/

according to below papers SIFT should outperform SURF in scale, blur and rotation ~~changes:~~ changes:

"A performance evaluation of SIFT and SURF for multispectral image ~~matching"~~ matching"

"A Comparison of SIFT, PCA-SIFT and SURF" Same Dataset has been ~~used.~~ used.

"SIFT and SURF Performance Evaluation Against Various Image Deformations on Benchmark Dataset"

i get below result for Bike (Blur) images

image description

i also used below codes for SIFT and SURF detector: (it's main code and not all of it) //Notice That SIFT and SURF code run separately and variables not getting overwrite.

SiftFeatureDetector detector;
detector.detect(img_1, key_points_1);
detector.detect(img_2, key_points_2);

int minHessian = 5000;             
SurfFeatureDetector detector(minHessian);   
detector.detect(img_1, key_points_1);
detector.detect(img_2, key_points_2);

cv::evaluateFeatureDetector(img_1c, img_2c, h12, &key_points_1, &key_points_2, repeatability, corrCounter); //H12 is homography matrix which was included in the Dataset

Did i miss something ? why my results is different?(also checked scale and rotation change and still SURF outperform SIFT)

How come Surf Detector is better than Sift in my code

Hi Hi i'm evaluating SIFT and SURF Detectors in my project with mikolajczyk Dataset. you can find it here:http://www.robots.ox.ac.uk/~vgg/research/affine/

according to below papers SIFT should outperform SURF in scale, blur and rotation changes:

"A performance evaluation of SIFT and SURF for multispectral image matching"

"A Comparison of SIFT, PCA-SIFT and SURF" Same Dataset has been used.

"SIFT and SURF Performance Evaluation Against Various Image Deformations on Benchmark Dataset"

i get below result for Bike (Blur) images

image description

i also used below codes for SIFT and SURF detector: (it's main code and not all of it) //Notice That SIFT and SURF code run separately and variables not getting overwrite.

SiftFeatureDetector detector;
detector.detect(img_1, key_points_1);
detector.detect(img_2, key_points_2);

int minHessian = 5000;             
SurfFeatureDetector detector(minHessian);   
detector.detect(img_1, key_points_1);
detector.detect(img_2, key_points_2);

cv::evaluateFeatureDetector(img_1c, img_2c, h12, &key_points_1, &key_points_2, repeatability, corrCounter); //H12 is homography matrix which was included in the Dataset

Did i miss something ? why my results is different?(also checked scale and rotation change and still SURF outperform SIFT)