2017-08-15 12:44:47 -0600 | received badge | ● Student (source) |
2016-08-03 17:03:47 -0600 | commented answer | What options are there for Dimensionality Reduction of HoG Descriptors What options would there be to scale the BoW (could I run in parallel and combine the output? Also wouldn't I need to aggregate the descriptor output of the frames if it was the action/sequence I was trying to train on not specific image elements, taking your pizza example from earlier instead of trying to identify a pizza, the aim would be to identify someone making a pizza instead of cooking a steak |
2016-08-03 05:56:04 -0600 | commented answer | What options are there for Dimensionality Reduction of HoG Descriptors Could I ask what you mean by |
2016-08-02 15:19:41 -0600 | commented answer | What options are there for Dimensionality Reduction of HoG Descriptors Thanks for the small light at the end of the tunnel regarding Kmeans. Any advice for dealing with the descriptors prior to BoW as while using python I'm running into memory issues due to the amount and size |
2016-08-02 06:44:07 -0600 | commented answer | What options are there for Dimensionality Reduction of HoG Descriptors Hi Guanta, Thanks for responding. My source images are video frames so wouldn't they have alot of similar descriptors as slight changes occur between frame x and x+ 1 and so if you were to sample the descriptors isn't there a possibility that the 100 samples per image would not be representative of the image detail and so could not be used to discriminate between images of different class ? |
2016-08-01 16:46:26 -0600 | asked a question | What options are there for Dimensionality Reduction of HoG Descriptors I have a very large number of HoG descriptors for 960x540 images and I was wondering if there was any recommendations I could take that would let me reduce the dimensionality of the HoG descriptors that are produced to make the dataset more manageable for BoW and KMeans and what the trade off against predictive accuracy could look like? |
2016-07-02 06:29:49 -0600 | asked a question | What options exist for removing Crowds/Audiences from Videos Could the community suggest methods for removing or reducing the influence crowds or audiences from videos as a preprocessing step? If you take this image as an discussion example and assume its a video of a game.
Could you flip the problem and remove everything thats not within X pixels of the dominate playing area colour and what would the OpenCV code for that look like?
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2016-06-10 04:00:53 -0600 | asked a question | OpenCV2 BatchDistance Error -215 when looping through images while individual comparisons work correctly I had asked this question on stackoverflow but now think this is a better place for it I have python code to use OpenCV2 (3.10) to calculate the features of 2 images, match then and plot the most similar points. If I run the individual code it works and I can manually change the 2nd image file and the code will plot the matches, My problem is when I try to automate it to loop through a directory of images to compare to the 1st image I get the following error on Ubuntu 14.04, OpenCV 3.10 and Python 2.7 Besides the roughness of my code, anyone see why the loop errors out but the individual comparisons don't? Individual Code Will match without triggering the error for every test image I supply by manually editing the 2nd image filepath value. Looping Code Below is code to loop through a directory, load the image into OpenCV, calculate the keypoints and features of the image and compare it to a search image before getting the number of matches and plotting the top 40 matches (more) |
2016-06-07 09:55:39 -0600 | commented question | How to access Scene Text Detection in OpenCV 3 in python ? Has the release of OpenCV 3.1 changed this and if so is scene text recognition also now available? |
2016-06-05 15:33:18 -0600 | commented question | Installing OpenCV2 on Ubuntu 14.04 - script failing on make install If I run the script on a Ubuntu Desktop vm I set up locally it completes properly but I need it to run on the hosted ubuntu server |
2016-06-04 10:49:23 -0600 | asked a question | Installing OpenCV2 on Ubuntu 14.04 - script failing on make install I have amended a script from https://github.com/jayrambhia/Install... to try to install 2.4.13 onto a vm running 14.04 where I have sudo permissions. I'm new to openCV so any help getting this script to work would be appreciated as I have to deploy 20 vm's with OpenCV After a few minutes of running the script returns with an error saying can't
and The last few lines of the output is included below and the script is before that. Any ideas why the script wont complete successfully as I need to install OpenCV on many vms Install Script Command Output (more) |
2016-06-04 05:14:19 -0600 | commented answer | OpenCV 3.1 Build for multiple virtual machines when you say install may be neccessary to link |
2016-06-04 05:13:05 -0600 | received badge | ● Supporter (source) |
2016-06-02 14:57:12 -0600 | asked a question | OpenCV 3.1 Build for multiple virtual machines If I build openc 3.1 on Ubuntu 14.04 with default jdk do I have to build it again to use on another virtual machine if the OS version is the same? |
2016-05-24 10:54:27 -0600 | commented question | Cascade Classifier Training: Train different object variants together or separate? Hi @aKzenT did you get an answer to your cascade training question ? |
2016-03-31 13:47:02 -0600 | received badge | ● Scholar (source) |
2016-03-30 14:56:17 -0600 | received badge | ● Editor (source) |
2016-03-30 14:40:32 -0600 | asked a question | OpenCV, Space Time Interest Points (STIP) & Camera Motion I understand the implementation of space(spatial) time(temporal) interest points by Laptev http://www.di.ens.fr/~laptev/download... required OpenCV but since the release of the updated STIP code in 2011 has OpenCV integrated the feature into its toolkit or does OpenCV have its own similar function and how susceptible are STIP methods to camera motion |
2016-03-19 07:03:25 -0600 | received badge | ● Enthusiast |
2016-03-15 01:26:27 -0600 | commented question | Detect Broadcasted Video using OpenCV It looks to be the same camera angle but that the TV producer adds the overlay then switches to a replay of action, the original shot is still available. I can't say for sure they are the same length till I find the TV feeds. I have multiple videos to process and possibly different overlays used as different TV stations involved |
2016-03-14 09:08:27 -0600 | asked a question | Detect Broadcasted Video using OpenCV How would I detect or identify videos using opencv as being the broadcast output from multiple video files ? Forgive me but I may not have the correct terminology but i guess what I'm asking is how do I inspect a video for tv channel overlays or graphics a broadcaster adds to the raw video that appear intermittently in a video like a channel logo ? And following that how do I compare 2 videos to know if video A is the broadcast then video G is the raw video without the graphics |
2016-02-10 10:42:33 -0600 | asked a question | Video / Image exploratory data analysis: OpenCV a good starting point Forgive the novice question but is OpenCV a good set of tools to start exploring a dataset of images/video or are there other tools that users would recommend instead to get a feel for a new dataset of images or video data? |