{"id":1934,"date":"2018-04-19T20:47:09","date_gmt":"2018-04-19T11:47:09","guid":{"rendered":"http:\/\/www.chihayafuru.jp\/tech\/?p=1934"},"modified":"2018-05-04T15:01:04","modified_gmt":"2018-05-04T06:01:04","slug":"opencv-detectmultiscale%e3%81%ae%e4%bd%bf%e3%81%84%e3%81%8b%e3%81%9f","status":"publish","type":"post","link":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/archives\/1934","title":{"rendered":"[OpenCV] detectMultiScale\u306e\u4f7f\u3044\u304b\u305f"},"content":{"rendered":"

OpenCV\u3067\u7269\u4f53\u691c\u51fa\uff08\u305f\u3068\u3048\u3070\u9854\u691c\u51fa\uff09\u3092\u3059\u308b\u3068\u304d\u306b\u4f7f\u7528\u3059\u308b detectMultiScale \u306e\u5f15\u6570\u306e\u610f\u5473\u3068\u4f7f\u3044\u304b\u305f\u3002
\n<\/p>\n

void CascadeClassifier::detectMultiScale(\r\n  const Mat& image,\r\n  vector& objects,\r\n  double scaleFactor=1.1,\r\n  int minNeighbors=3,\r\n  int flags=0,\r\n  Size minSize=Size())<\/pre>\n
 <\/p>\n
1. image<\/h3>\n
CV_8U \u578b\u306e\u884c\u5217\uff0e\u3053\u3053\u306b\u683c\u7d0d\u3055\u308c\u3066\u3044\u308b\u753b\u50cf\u4e2d\u304b\u3089\u7269\u4f53\u304c\u691c\u51fa\u3055\u308c\u307e\u3059<\/p>\n
 <\/p>\n
2. objects<\/h3>\n
\u77e9\u5f62\u3092\u8981\u7d20\u3068\u3059\u308b\u30d9\u30af\u30c8\u30eb\uff0e\u305d\u308c\u305e\u308c\u306e\u77e9\u5f62\u306f\uff0c\u691c\u51fa\u3057\u305f\u7269\u4f53\u3092\u542b\u307f\u307e\u3059<\/p>\n
 <\/p>\n
3. scaleFactor<\/h3>\n
\u5404\u753b\u50cf\u30b9\u30b1\u30fc\u30eb\u306b\u304a\u3051\u308b\u7e2e\u5c0f\u91cf\u3092\u8868\u3057\u307e\u3059<\/p>\n\n\n\n
\u8a2d\u5b9a\u7bc4\u56f2<\/td>\n1.0\u3092\u8d85\u3048\u308b ( > 1.0 )<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
scaleFactor\u306f\u7e2e\u5c0f\u91cf\u306e\u300c\u30b9\u30c6\u30c3\u30d7\u300d\u3002\u3057\u305f\u304c\u3063\u3066scaleFactor\u304c\u5927\u304d\u304f\u306a\u308b\u307b\u3069\u98db\u3073\u98db\u3073\u306e\u8a08\u7b97\u306b\u306a\u308b\u3002\u7d50\u679c\u3068\u3057\u3066\u5168\u4f53\u3068\u3057\u3066\u306e\u8a08\u7b97\u304c\u901f\u304f\u306a\u308b\uff08\u8a08\u7b97\u6642\u9593\u304c\u77ed\u304f\u306a\u308b\uff09\u3002
\n\u30b9\u30c6\u30c3\u30d7\u3092\u7d30\u304b\u304f\u523b\u3080\u3053\u3068\uff08\u9650\u308a\u306a\u304f1.0\u306b\u8fd1\u3044\u5024\uff09\u304c\u826f\u3044\u8a33\u3067\u306f\u306a\u3044\u304c\u3001\u304b\u3068\u3044\u3063\u3066\u30b9\u30c6\u30c3\u30d7\u304c\u5927\u304d\u3044\u3068\u691c\u51fa\u300e\u898b\u9003\u3057\u300f\u304c\u767a\u751f\u3059\u308b\u3002<\/p>\n
 <\/p>\n
4. minNeighbors<\/h3>\n
\u7269\u4f53\u5019\u88dc\u3068\u306a\u308b\u77e9\u5f62\u306f\uff0c\u6700\u4f4e\u3067\u3082\u3053\u306e\u6570\u3060\u3051\u306e\u8fd1\u508d\u77e9\u5f62\u3092\u542b\u3080\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059<\/p>\n\n\n\n\n
0\u306e\u3068\u304d<\/td>\n\u691c\u51fa\u306b\u30de\u30c3\u30c1\u3059\u308b\u6570\u304c\u591a\u304f\u306a\u308b\u3002\u898b\u9003\u3057\u306f\u5c11\u306a\u3044\u304c\u8aa4\u691c\u51fa\u304c\u5897\u3048\u308b<\/td>\n<\/tr>\n
\u5927\u304d\u3044\u3068\u304d<\/td>\n\u691c\u51fa\u306b\u30de\u30c3\u30c1\u3059\u308b\u6570\u306f\u5c11\u306a\u304f\u306a\u308b\u3002\u898b\u9003\u3057\u306f\u591a\u3044\u304c\u8aa4\u691c\u51fa\u306f\u5c11\u306a\u3044<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
 <\/p>\n
5. flags<\/h3>\n
\u3053\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306f\uff0c\u65b0\u3057\u3044\u30ab\u30b9\u30b1\u30fc\u30c9\u3067\u306f\u5229\u7528\u3055\u308c\u307e\u305b\u3093\uff0e\u53e4\u3044\u30ab\u30b9\u30b1\u30fc\u30c9\u306b\u5bfe\u3057\u3066\u306f\uff0c<\/p>\n
 <\/p>\n
6. cvHaarDetectObjects<\/h3>\n
\u95a2\u6570\u306e\u5834\u5408\u3068\u540c\u3058\u610f\u5473\u3092\u6301\u3061\u307e\u3059<\/p>\n
 <\/p>\n
7. minSize<\/h3>\n
\u7269\u4f53\u304c\u53d6\u308a\u5f97\u308b\u6700\u5c0f\u30b5\u30a4\u30ba\uff0e\u3053\u308c\u3088\u308a\u3082\u5c0f\u3055\u3044\u7269\u4f53\u306f\u7121\u8996\u3055\u308c\u307e\u3059<\/p>\n
 <\/p>\n
\n
 <\/p>\n
ROI<\/strong> : Range Of Interest
\n\u753b\u50cf\u306e\u4e00\u90e8\u306b\u6ce8\u76ee\u3059\u308b\uff08\u5bfe\u8c61\u306b\u3059\u308b\uff09\u30ad\u30fc\u30ef\u30fc\u30c9<\/p>\n","protected":false},"excerpt":{"rendered":"
OpenCV\u3067\u7269\u4f53\u691c\u51fa\uff08\u305f\u3068\u3048\u3070\u9854\u691c\u51fa\uff09\u3092\u3059\u308b\u3068\u304d\u306b\u4f7f\u7528\u3059\u308b detectMultiScale \u306e\u5f15\u6570\u306e\u610f\u5473\u3068\u4f7f\u3044\u304b\u305f\u3002<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[50],"class_list":["post-1934","post","type-post","status-publish","format-standard","hentry","category-memo","tag-opencv"],"_links":{"self":[{"href":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/wp-json\/wp\/v2\/posts\/1934","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/wp-json\/wp\/v2\/comments?post=1934"}],"version-history":[{"count":14,"href":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/wp-json\/wp\/v2\/posts\/1934\/revisions"}],"predecessor-version":[{"id":2274,"href":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/wp-json\/wp\/v2\/posts\/1934\/revisions\/2274"}],"wp:attachment":[{"href":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/wp-json\/wp\/v2\/media?parent=1934"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/wp-json\/wp\/v2\/categories?post=1934"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.chihayafuru.jp\/tech\/index.php\/wp-json\/wp\/v2\/tags?post=1934"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}