SelectiveSearch
所属分类：数值算法/人工智能
开发工具：WINDOWS
文件大小：296KB
下载次数：20
上传日期：2017-07-25 09:42:17
上 传 者：
zouwit
说明： 采用matlab编程，根据图像中纹理、梯度、亮度等信息提取图片中候选区域做目标检测，平均检测速度为30fps
(Using MATLAB programming, according to the image texture, gradient, brightness and other information extraction of candidate areas in the image for target detection, the average detection speed of 30fps)
文件列表:
SelectiveSearchCodeIJCV (0, 2013-06-14)
SelectiveSearchCodeIJCV\Image2HierarchicalGrouping.m (3640, 2013-06-14)
SelectiveSearchCodeIJCV\MergeBlobs.p (398, 2013-05-31)
SelectiveSearchCodeIJCV\SSSimColourSize.p (165, 2013-05-31)
SelectiveSearchCodeIJCV\License.txt~ (2690, 2012-01-09)
SelectiveSearchCodeIJCV\BlobStruct2HierarchicalGrouping.p (922, 2013-05-31)
SelectiveSearchCodeIJCV\demoPascal2007.m (4346, 2013-06-03)
SelectiveSearchCodeIJCV\SSSimBoxFill.p (240, 2013-05-31)
SelectiveSearchCodeIJCV\SSSimTextureSize.p (164, 2013-05-31)
SelectiveSearchCodeIJCV\License.txt (2674, 2013-06-14)
SelectiveSearchCodeIJCV\demo.m (2943, 2013-06-01)
SelectiveSearchCodeIJCV\SSSimBoxFillOrigSize.p (171, 2013-05-31)
SelectiveSearchCodeIJCV\BoxAverageBestOverlap.m (1447, 2013-06-14)
SelectiveSearchCodeIJCV\ChangeEdges.p (187, 2013-05-31)
SelectiveSearchCodeIJCV\BlobAverageBestOverlap.m (2611, 2013-06-14)
SelectiveSearchCodeIJCV\mexFelzenSegmentIndex.mexa64 (22290, 2013-05-31)
SelectiveSearchCodeIJCV\BlobBestOverlap.m (751, 2013-06-14)
SelectiveSearchCodeIJCV\RecreateBlobHierarchy.m (929, 2013-06-14)
SelectiveSearchCodeIJCV\Dependencies (0, 2013-06-03)
SelectiveSearchCodeIJCV\Dependencies\gaussianFilter.p (377, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\Rgb2Rgi.p (238, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\mexCountWordsIndex.cpp (1704, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\Vector2Hist.p (251, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\Image2ColourSpace.p (592, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\Blobs2Boxes.p (148, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\SegmentIndices2Blobs.p (286, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\GetPascalOverlap.m (701, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\BoxIntersection.m (645, 2013-06-14)
SelectiveSearchCodeIJCV\Dependencies\FilterBoxesWidth.m (532, 2013-06-14)
SelectiveSearchCodeIJCV\Dependencies\PascalOverlap.m (948, 2013-06-14)
SelectiveSearchCodeIJCV\Dependencies\ShowImageCell.m (1493, 2013-06-14)
SelectiveSearchCodeIJCV\Dependencies\FelzenSegment (0, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\FelzenSegment\segment.cpp (1460, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\FelzenSegment\segment-graph.h (2191, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\FelzenSegment\imutil.h (1714, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\FelzenSegment\mexFelzenSegmentIndex.cpp (7971, 2013-06-14)
SelectiveSearchCodeIJCV\Dependencies\FelzenSegment\disjoint-set.h (1857, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\FelzenSegment\convolve.h (2009, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\FelzenSegment\pnmfile.h (5464, 2013-05-31)
SelectiveSearchCodeIJCV\Dependencies\FelzenSegment\image.h (2395, 2013-05-31)
... ...
Implementation of the segmentation algorithm described in:
Efficient Graph-Based Image Segmentation
Pedro F. Felzenszwalb and Daniel P. Huttenlocher
International Journal of Computer Vision, 59(2) September 2004.
The program takes a color image (PPM format) and produces a segmentation
with a random color assigned to each region.
1) Type "make" to compile "segment".
2) Run "segment sigma k min input output".
The parameters are: (see the paper for details)
sigma: Used to smooth the input image before segmenting it.
k: Value for the threshold function.
min: Minimum component size enforced by post-processing.
input: Input image.
output: Output image.
Typical parameters are sigma = 0.5, k = 500, min = 20.
Larger values for k result in larger components in the result.
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