enienws's profile - activity

overview network karma followed questions activity

2020-12-22 20:55:11 -0600	received badge	● Popular Question (source)
2013-09-03 02:58:02 -0600	received badge	● Nice Question (source)
2013-07-30 02:03:35 -0600	commented question	Test failures with Intel compiler Have you found any solution to this problem? I have the same problem that is I have built OpenCV with icc compiler and accuracy tests are failed.
2013-07-30 02:00:21 -0600	received badge	● Supporter (source)
2013-07-22 02:34:23 -0600	asked a question	OpenCV and Intel's C++ Compiler Is there any one who had built OpenCV with Intel's C++ compiler? Which compiler flags should be used for OpenCV compilation to get best performance from library? I want to benefit from vectorization properties of compiler and want machine code of OpenCV which fully benefits SSE and AVX instructions. At least some clues about this issue will be fine for me. Regards.
2013-07-22 02:31:10 -0600	commented question	Bencmarking on Different OpenCV Builds berak, Shervin's post is valueable. But I am looking for something different. I think similiar to StevenPuttermans. I have built performance code when building OpenCV. Under the bin folder in build folder I have found some executables which are aimed to measure performance of different tasks. The following is the list of these executables: opencv_perf_calib3d opencv_perf_nonfree opencv_perf_stitching opencv_perf_core opencv_perf_objdetect opencv_perf_superres opencv_perf_features2d opencv_perf_ocl opencv_perf_video opencv_perf_highgui opencv_performance opencv_perf_imgproc opencv_perf_photo So I have decided to write a python script to run these different performace executables and then writing all test results to a csv file.
2013-07-22 02:06:16 -0600	commented answer	Files needed by performance executables Thank you so much!!
2013-07-19 14:46:33 -0600	asked a question	Files needed by performance executables Hello folks, I need to profile performance of different builds of OpenCV. So to do this, I have built performance programsa of OpenCV: opencv_perf_calib3d opencv_perf_nonfree opencv_perf_stitching opencv_perf_core opencv_perf_objdetect opencv_perf_superres opencv_perf_features2d opencv_perf_ocl opencv_perf_video opencv_perf_highgui opencv_performance opencv_perf_imgproc opencv_perf_photo But these executables need some files which I cannot find them. For example, opencv_perf_calib3d executable needs "cv/cameracalibration/asymmetric_circles/acircles1.png" file but I cannot find this file and other files which are required by other performance modules. Where can I find these files?
2013-07-17 06:28:47 -0600	asked a question	Bencmarking on Different OpenCV Builds Hello, I am planning to build OpenCV with different methods, such as with or without IPP, with gcc or icc etc. I think on a benchmark application by using these different builds of OpenCV. But I cannot find a considerable way to handle this? Could you please advice some techniques to use for this purpose? Regards.
2012-12-29 04:55:46 -0600	commented answer	How to track human face? Yes I am using that methodologies too. There is no problem about finding a new face region. The problem is that, when program lost a face - due to occlusion or something else, and then that face detected again with a LBP face detection, I need to classify that face. For example let a face is identified by number id 1000. Due to some occlusions this face is lost by camshift tracker. Then this face is detected again LBP classifer. At that time, I need to classify face and need to give it id 1000 not 1001. I have been researching about feature descriptors and a score generated by matching these descriptors. The question is that whether this is a convenient way or not?
2012-12-28 12:13:10 -0600	commented answer	How to track human face? Actually I am using Camshift for tracking faces. Moreover I have implemented some features to solve camshift's occlusion problem and some problems related with camshift. So, program stops tracking for some cases. My face classification problem arises here.
2012-12-28 10:24:49 -0600	asked a question	How to track human face? Hello, I have been working on a project which tracks multiple faces in video sequences. My tracking algorithm may stop tracking for some cases (i.e. occlusion). So to give same ID to the lost face on next frames I want to match new detected face with a face which is lost in previous frames. For example a short-term memory like ~3 seconds is just enough for me. To implement this feature I have been researching on feature descriptors and a score generated by matching these descriptors. I am curious about whether this is a reasonable way for solving this problem? If not could you give some advices on this issue? Best wishes.
2012-12-23 08:34:48 -0600	commented answer	Question About Histogram Comparison Thank you so much. I have understood where the mistake was.
2012-12-23 08:34:03 -0600	received badge	● Scholar (source)
2012-12-23 07:28:15 -0600	received badge	● Student (source)
2012-12-22 10:47:06 -0600	asked a question	Question About Histogram Comparison Hello, I need to compare two histograms for my project. I am working on normalized histograms by using the following function call: `//Assuming that histogram is a cv::Mat and is valid cv::normalize(histogram, histogram, 1.0);` I am using cv::compareHist() to compare the histograms. I have tried the all four methods for comparison with OpenCV macros: CV_COMP_CORREL, CV_COMP_CHISQR, CV_COMP_INTERSECT, CV_COMP_BHATTACHARYYA. The problem is that: When analyzing the comparison results, CV_COMP_INTERSECT comparison method produce values bigger than 1 although two histograms are normalized. It is stated on Learning OpenCV: Computer Vision with the OpenCV library (page 202): If both histograms are normalized to 1, then a perfect match is 1 and a total mismatch is 0. What you think about this? Best wishes.