{"product_id":"face-recognition-principal-component-analysis-method-algorithm-simulation-discussion-von-liton-chandra-paul-abdulla-al-suman","title":"Face Recognition \u0026 Principal Component Analysis Method","description":"\u003cp\u003eThis book mainly addresses the building of face recognition system and Principal Component Analysis (PCA) method in details. PCA is a statistical approach used for reducing the number of variables in face recognition. In PCA, every image in the training set is represented as a linear combination of weighted eigenvectors called eigenfaces. These eigenvectors are obtained from covariance matrix of a training image set called as basis function. The weights are found out after selecting a set of most relevant Eigenfaces. Recognition is performed by projecting a test image onto the subspace spanned by the eigenfaces and then classification is done by measuring Euclidean distance. A number of experiments were done to evaluate the performance of the face recognition system. Here, I used a training database of students of ETE-07 series, RUET, Rajshahi-6204, Bangladesh.\u003c\/p\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783659461453\"\u003e\u003ch3\u003eAlgorithm, Simulation \u0026amp; Discussion\u003c\/h3\u003e\u003c\/div\u003e","brand":"Libri","offers":[{"title":"Softcover - 9783659461453","offer_id":39434239410269,"sku":"9783659461453","price":39.9,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/ef24633f-5f8b-4412-a1ff-46203e2ef9eb.jpg?v=1770099500","url":"https:\/\/shop.autorenwelt.de\/products\/face-recognition-principal-component-analysis-method-algorithm-simulation-discussion-von-liton-chandra-paul-abdulla-al-suman","provider":"Autorenwelt Shop","version":"1.0","type":"link"}