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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Algorithm for Head Comparison in Non-Standard Views
 Wysoglad, Jaromír ; Goldmann, Tomáš (referee) ; Drahanský, Martin (advisor)
The goal of this work is to create an algorithm for human head comparison. The algorithm is able to compare heads in a lot of different positions, but the heads, that are being compared, must be in the same position. At first the algorithm uses some freely available detectors for detecting heads and head parts. Then a histogram of oriented gradients is computed for each part of each head and by comparing them the algorithm finds out the dissimilarity of the heads. From the testing set of 30 pictures the algorithm is able to successfully detect heads on 26 pictures. Every picture was compared with 5 other pictures, with one of them containing a head of the same person. If I don't count the 4 pictures, where the algorithm wasn't able to detect the head and 2 pictures, which should have been assigned to these pictures. The algorithm successfully determined, that the head of the same person is the most similar on 18 pictures. On 5 pictures the head of the same person was determined as the 3rd most similar and on one of the pictures the algorithm failed completely and determined the head of the same person to be the least similar. The algorithm is successful with head comparison in different positions on most of the pictures.
Detailed record
Algorithm for Head Comparison in Non-Standard Views
 Wysoglad, Jaromír ; Goldmann, Tomáš (referee) ; Drahanský, Martin (advisor)
The goal of this work is to create an algorithm for human head comparison. The algorithm is able to compare heads in a lot of different positions, but the heads, that are being compared, must be in the same position. At first the algorithm uses some freely available detectors for detecting heads and head parts. Then a histogram of oriented gradients is computed for each part of each head and by comparing them the algorithm finds out the dissimilarity of the heads. From the testing set of 30 pictures the algorithm is able to successfully detect heads on 26 pictures. Every picture was compared with 5 other pictures, with one of them containing a head of the same person. If I don't count the 4 pictures, where the algorithm wasn't able to detect the head and 2 pictures, which should have been assigned to these pictures. The algorithm successfully determined, that the head of the same person is the most similar on 18 pictures. On 5 pictures the head of the same person was determined as the 3rd most similar and on one of the pictures the algorithm failed completely and determined the head of the same person to be the least similar. The algorithm is successful with head comparison in different positions on most of the pictures.
Detailed record

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