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- W2605291162 abstract "This paper aims to address a mechanism to recognize and classify the faces present in the videos. The number of videos are collected from the different sources. Each of the videos are divided into frames which are images. Key frames are extracted and stored in a separate directory. From the extracted key frames, faces present in them are detected. These set of faces detected will be used as a training data-set which are stored in normal directory. The features from each of the face images are extracted by making use of Local Binary Patterns (LBP). The feature values will further be used to train the Support Vector Machine (SVM) classifier. In the testing phase, the same process is carried out and SVM makes the prediction based on the training data-set to which class the face belongs to. The effectiveness of the proposed system’s prediction is demonstrated by collecting different video data-set and the accuracy of the model is comparable." @default.
- W2605291162 created "2017-04-14" @default.
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- W2605291162 date "2017-01-01" @default.
- W2605291162 modified "2023-09-25" @default.
- W2605291162 title "Face Identification and Face Classification Using Computer Vision and Machine Learning Algorithm" @default.
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- W2605291162 doi "https://doi.org/10.1007/978-3-319-57261-1_28" @default.
- W2605291162 hasPublicationYear "2017" @default.
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