B. Bogart's profile - overview

overview network karma followed questions activity

119

karma

Registered User
member since	2013-06-06 18:20:35 -0600
last seen	2020-01-09 12:08:00 -0600
todays unused votes	60 votes left

9 Questions

46k

views

5

answers

3

votes

2015-11-19 14:28:20 -0600 matman

What is the best practise for passing cv::Mats around

#Mat

12k

views

1

answer

1

vote

2014-04-10 11:51:55 -0600 B. Bogart

Fastest way to apply alpha channel to image

251

views

no

answers

1

vote

2019-12-20 12:03:03 -0600 B. Bogart

pretrained model for gaze / frontal face detection for cv::dnn?

2k

views

no

answers

no

votes

2013-07-11 13:00:26 -0600 B. Bogart

Memory leak on Mat creation

144

views

no

answers

no

votes

2013-09-16 18:13:46 -0600 B. Bogart

How to replace an instance with cv::Mat members with another instance via pointer?

Mat

1k

views

no

answers

no

votes

2013-08-29 19:23:32 -0600 B. Bogart

How to run findContours() on meanShiftSegmentation() output? [deleted]

2k

views

2

answers

no

votes

2013-08-21 20:02:08 -0600 B. Bogart

Bug? Increasing memory usage per iteration when using findContours()

1k

views

1

answer

no

votes

2013-07-17 19:17:51 -0600 berak

Deep copy of list of instances with cv::Mat members

#Mat

3k

views

3

answers

no

votes

2014-02-21 11:20:54 -0600 B. Bogart

Debugging memory leak related to instance with cv::Mat members

4 Answers

Fastest way to apply alpha channel to image

Efficient Alpha Blending

What is the best practise for passing cv::Mats around

Debugging memory leak related to instance with cv::Mat members

4 Votes

3

1

18 Tags

#memoryleak× 13
#Mat× 12
#cvMat× 10
findContours× 7
clone× 6
alpha-blending× 4
blending× 3
optimization× 2
alpha-channel× 2
python× 1
Mat× 1
segmentation× 1
yaml× 1
Facedetection× 1
eye× 1
meanshift× 1
dnn× 1
c++#dnn#opencv× 1

13 Badges

● Supporter × 1 ● Editor × 1 ● Self-Learner × 1
● Student × 1 ● Scholar × 1 ● Critic × 1
● Notable Question × 2 ● Teacher × 1 ● Nice Answer × 1
● Necromancer × 1 ● Nice Question × 1 ● Famous Question × 2
● Popular Question × 4

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