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Trajectory-pooled Deep-Convolutional Descriptors
Hi, @wanglimin
I want to reproduce the experiment result in the paper.
And I found a parameter named 'power' in extract_fv.m. The use of this para is setting feature to feature.^power before coding.
What's the value of this para should I set in order to reproduce the result?
Thanks.
Hi, LiMin.
What's the meaning of sizes in line 19 of script_demo
sizes = [8,8; 11.4286,11.4286; 16,16; 22.8571,24;32,34.2587];%why?
In my opinion, according to your paper, sizes shold be
[16*1/2,16*1/2; 16*1/sqrt(2), 16*1/sqrt(2); 16,16;16*sqrt(2),16*sqrt(2);16*2,16*2]
Am I misunderstanding something?
Hi, @wanglimin
Have you encountered the problem of unbalanced category accuracy while training and testing on HMDB51 dataset? For example, the accuracy of the class "kick" is much better than the class "brush_hair" in HMDB51 dataset while testing.
Thanks,
Philip
Hi, LiMin
The code in FlowCNNFeature.m
function FCNNFeature = FlowCNNFeature(vid_name, use_gpu, NUM_HEIGHT, NUM_WIDTH, model_def_file, model_file, gpu_id)
L = 10;
% Input video
filelist =dir([vid_name,'*_x*.jpg']);
if length(filelist) > 30 *60
video = zeros(NUM_HEIGHT,NUM_WIDTH,L*2,30*60,'single');
else
video = zeros(NUM_HEIGHT,NUM_WIDTH,L*2,length(filelist),'single');
end
for i = 1:size(video,4)
flow_x = imread(sprintf('%s_%06d.jpg',[vid_name,'flow_x'],i));
flow_y = imread(sprintf('%s_%06d.jpg',[vid_name,'flow_y'],i));
video(:,:,1,i) = imresize(flow_x,[NUM_HEIGHT,NUM_WIDTH],'bilinear');
video(:,:,2,i) = imresize(flow_y,[NUM_HEIGHT,NUM_WIDTH],'bilinear');
end
for i = 1:L-1%
tmp = cat(4, video(:,:,(i-1)*2+1:i*2,2:end),video(:,:,(i-1)*2+1:i*2,end));%240*320*2*54
video(:,:,i*2+1:i*2+2,:) = tmp;
end
I find it hard to understand the code
for i = 1:L-1%
tmp = cat(4, video(:,:,(i-1)*2+1:i*2,2:end),video(:,:,(i-1)*2+1:i*2,end));%
video(:,:,i*2+1:i*2+2,:) = tmp;
end
For example there are 55 frames in a video, so the variable video's shape is (240 320 20 55).
For every frame, there are 20 flow images with size 240*320 corresponds to it.
According to the code, for every frame, the first two flow image are flow_x and flow_y, the remaining 18 flow images are just the copy of the first two?
Does this make sense?
Why not just use
tmp =video(:,:,(i-1)*2+1:i*2,1:end);
Hi @wanglimin
Thanks
Raymond
The elements of flow_mean.mat are all zeros?
Hi, @wanglimin
I want to know how to generate the ‘PCA’ in extract_fv.m
Thanks
Hi, LiMin
When I run script_demo.m
>> script_demo
Extract improved trajectories...
video size, length: 55, width: 320, height: 240
Extract TVL1 optical flow field...
Extract spatial TDD...
Undefined function 'caffe' for input arguments of type 'char'.
Error in RGBCNNFeature (line 18)
if caffe('is_initialized') == 0
Error in script_demo (line 32)
feature_conv = RGBCNNFeature(vid_name, 1, sizes_vid(scale,1), sizes_vid(scale,2), model_def_file, model_file, gpu_id);
what's wrong? I am using the latest version of caffe.
Thank you very much!
Click on the Spatial net model(v2) can`t download ,how i can download the two models? look forward to your answer!
Hello @wanglimin
I have download your modified iDT feature code and compiled it in the release mode by myself in VS2013 win10, then I have the .exe file .
I can not understand why Some videos in 'hmdb51_sta.' have different number of trajectories and features in Matlab using the command system(['./DenseTrackStab -f ',vid_name,' -o ',vid_name(1:end-4),'.bin']) compared with running the code in vs12013.
Thanks,
Mark
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