10/22/2015
More stringent pedestrian detectionby Deep learning verification
Labels:
Pedestrian detection,
Pedestrian tracking,
Total,
Tracking
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The MNIST dataset is a dataset of handwritten digits, comprising 60 000 training examples and 10 000 test examples. The dataset can be downl...
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Image size of origin is 320*240. Processing time is 30.96 second took. The result of stitching The resul...
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In past, I wrote an articel about YUV 444, 422, 411 introduction and yuv <-> rgb converting example code. refer to this page -> ht...
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Download for free https://www.spectacleapp.com/ I like it. ๐๐ป♂️
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In the YUV color format, Y is bright information, U is blue color area, V is red color area. Show the below picture. The picture is u-v col...
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error: . VanillaPipeline.get_train_loss_dict: 12.6875 Traceback (most recent call last): File "/home/mare/anaconda3...
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* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm...
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fig 1. Left: set 4 points (Left Top, Right Top, Right Bottom, Left Bottom), right:warped image to (0,0) (300,0), (300,300), (0,300) Fi...
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As you can see in the following video, I created a class that stitching n cameras in real time. https://www.youtube.com/user/feelmare/sear...
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EMD(earth mover distance) method is very good method to compare image similarity. But processing time is slow. For using the EMD compare, ...
Hello Kim,
ReplyDeleteI am trying to achieve same thing with Raspberrypi and HOG+SVM 320x240 body it seems too slow to me . So my query is that if i want to achieve Realtime tracking upper body and face detection minimum Hardware requirement for.