PERSON REIDENTIFICATION USING MCE-KISS METRIC LEARNING WITH MAXIMUM LIKELIHOOD FUNCTION - G M, Sree Vrinda; Jayaprakash, Dr. P. (IJRDO -Journal of Computer Science Engineering, 2016)
Nowadays, in the area of IntelligentVideo Surveillance (IVR), person reidentificationreceives an intensive attention. Personreidentification aims to match an instance of aperson captured by one camera system to theinstance of a person captured by another camerasystem. It is considered as a challenging problembecause the appearance of person varies throughthe scenes, lightning conditions, shadows,different pose of person that has to be searchedfor. Recently, many algorithms proposed likeLMNN, ITML are not suitable for large trainingsamples. This paper introduces MinimumClassification Error (MCE) based KISS metricalgorithm with smoothing technique to improvereidentification. Smoothing technique is donewith maximum likelihood functions whichenlarge small eigenvalues in the estimatedcovariance matrices.