HOG描述器最重要的思想是:在一副图像中,局部目标的表象和形状(appearance and
shape)能够被梯度或边缘的方向密度分布很好地描述。具体的实现方法是:首先将图像分成小的连通区域,我们把它叫细胞单元。然后采集细胞单元中各像素点的梯度的或边缘的方向直方图。最后把这些直方图组合起来就可以构成特征描述器。为了提高性能,我们还可以把这些局部直方图在图像的更大的范围内(我们把它叫区间或block)进行对比度归一化(contrast-normalized),所采用的方法是:先计算各直方图在这个区间(block)中的密度,然后根据这个密度对区间中的各个细胞单元做归一化。通过这个归一化后,能对光照变化和阴影获得更好的效果。
SHOW FULL COLUMNS FROM `jrk_downrecords` [ RunTime:0.001965s ]
SELECT `a`.`aid`,`a`.`title`,`a`.`create_time`,`m`.`username` FROM `jrk_downrecords` `a` INNER JOIN `jrk_member` `m` ON `a`.`uid`=`m`.`id` WHERE `a`.`status` = 1 GROUP BY `a`.`aid` ORDER BY `a`.`create_time` DESC LIMIT 10 [ RunTime:0.088470s ]
SHOW FULL COLUMNS FROM `jrk_tagrecords` [ RunTime:0.001115s ]
SELECT * FROM `jrk_tagrecords` WHERE `status` = 1 ORDER BY `num` DESC LIMIT 20 [ RunTime:0.001420s ]
SHOW FULL COLUMNS FROM `jrk_member` [ RunTime:0.002922s ]
SELECT `id`,`username`,`userhead`,`usertime` FROM `jrk_member` WHERE `status` = 1 ORDER BY `usertime` DESC LIMIT 10 [ RunTime:0.003364s ]
SHOW FULL COLUMNS FROM `jrk_searchrecords` [ RunTime:0.001018s ]
SELECT * FROM `jrk_searchrecords` WHERE `status` = 1 ORDER BY `num` DESC LIMIT 5 [ RunTime:0.004157s ]
SELECT aid,title,count(aid) as c FROM `jrk_downrecords` GROUP BY `aid` ORDER BY `c` DESC LIMIT 10 [ RunTime:0.028349s ]
SHOW FULL COLUMNS FROM `jrk_articles` [ RunTime:0.001513s ]
UPDATE `jrk_articles` SET `hits` = 2 WHERE `id` = 22160 [ RunTime:0.017769s ]