64 lines
2.0 KiB
Matlab
64 lines
2.0 KiB
Matlab
function pyra = featpyramid(im, model)
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% pyra = featpyramid(im, model, padx, pady);
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% Compute feature pyramid.
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%
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% pyra.feat{i} is the i-th level of the feature pyramid.
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% pyra.scales{i} is the scaling factor used for the i-th level.
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% pyra.feat{i+interval} is computed at exactly half the resolution of feat{i}.
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% first octave halucinates higher resolution data.
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interval = model.interval;
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sbin = model.sbin;
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% Select padding, allowing for one cell in model to be visible
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% Even padding allows for consistent spatial relations across 2X scales
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padx = max(model.maxsize(2)-1-1,0);
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pady = max(model.maxsize(1)-1-1,0);
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%padx = model.maxsize(2);
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%pady = model.maxsize(1);
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% padx = ceil(padx/2)*2;
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% pady = ceil(pady/2)*2;
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sc = 2 ^(1/interval);
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imsize = [size(im, 1) size(im, 2)];
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% max_scale = 1 + floor(log(min(imsize)/(5*sbin))/log(sc));
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max_scale = 0;
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pyra.feat = cell(max_scale + interval, 1);
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pyra.scale = zeros(max_scale + interval, 1);
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% our resize function wants floating point values
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im = double(im);
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for i = 1:interval
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scaled = resize(im, 1/sc^(i-1));
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% "first" 2x interval
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pyra.feat{i} = features(scaled, sbin/2);
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pyra.scale(i) = 2/sc^(i-1);
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% "second" 2x interval
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pyra.feat{i+interval} = features(scaled, sbin);
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pyra.scale(i+interval) = 1/sc^(i-1);
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% remaining interals
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for j = i+interval:interval:max_scale
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scaled = reduce(scaled);
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pyra.feat{j+interval} = features(scaled, sbin);
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pyra.scale(j+interval) = 0.5 * pyra.scale(j);
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end
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end
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for i = 1:length(pyra.feat)
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% add 1 to padding because feature generation deletes a 1-cell
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% wide border around the feature map
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pyra.feat{i} = padarray(pyra.feat{i}, [pady+1 padx+1 0], 0);
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% write boundary occlusion feature
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pyra.feat{i}(1:pady+1, :, end) = 1;
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pyra.feat{i}(end-pady:end, :, end) = 1;
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pyra.feat{i}(:, 1:padx+1, end) = 1;
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pyra.feat{i}(:, end-padx:end, end) = 1;
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end
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pyra.scale = model.sbin./pyra.scale;
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pyra.interval = interval;
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pyra.imy = imsize(1);
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pyra.imx = imsize(2);
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pyra.pady = pady;
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pyra.padx = padx; |