Teknomo–Fernandez algorithm: Difference between revisions

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==Time Complexity==

The entire algorithm runs in <math>O(R</math>)-time, only depending on the resolution of the image. Computing the modal bit for each bit can be done in <math>O(1)</math>-time while the computation of the resulting image from the three given images can be done in <math>O(R)</math>-time. The number of the images to be processed in <math>L</math> levels is <math>O(3^L)</math>. However, since <math>L \le 6</math>, then this is actually <math>O(1)</math>, thus the algorithm runs in <math>O(R)</math>.<ref name="TF" />

==Variants==

A variant of the [[Teknomo-Fernandez Algorithm]] that incorporates the [[Monte-Carlo method]] named CRF has been developed. Two different configurations of CRF were implemented: CRF9,2 and CRF81,1. Experiments on some colored video sequences showed that the CRF configurations outperform the [[TF Algorithm]] in terms of accuracy. However, the [[TF Algorithm]] remains more efficient in terms of processing time. <ref name="CRF">{{cite journal | last1 = Abu | first1 = Patricia Angela | last2 = Chu | first2 = Varian Sherwin| last3 = Fernandez | first3 = Proceso| title = A Monte-Carlo-based Algorithmfor Background Generation | url =https://www.researchgate.net/publication/273391116_A_Monte-Carlo-based_Algorithm_for_Background_Generation}}</ref>

==Applications==

* [[Object detection]]

* [[Face detection]]

* [[Face recognition]]

* [[Pedestrian detection]]

* [[Video surveillance]]

* [[Motion capture]]

* [[Human-computer interaction]]

* Content based Video Coding

* Traffic monitoring

* Real-time [[Gesture recognition]]

==References==