1. A computer implemented method for enhancing accuracy of real-time human counting in at least one frame of a captured image in a predefined viewing area, the method comprising steps of: detecting, by a processor, a human in one or more frames by using a plurality of human detection modalities, each of the plurality of human detection modalities obtaining a characteristic result of the said captured image; calculating, by the processor, an accuracy probability of each of the plurality of human detection modalities by evaluating each of the obtained characteristic results of the plurality of human detection modalities and using a pre calculated value of an activity probability of the plurality of human detection modalities, the activity probability adapted to determine a variance in detected human count in each frame; generating, by the processor, a combination of the obtained characteristic results of the plurality of human detection modalities by using a Bayesian fusion technique; selectively integrating, by the processor, the obtained characteristic results for each frame from the combination of the plurality of human detection modalities and the activity probability associated with the plurality of human detection modalities by using a regression model, wherein mean and standard deviation values of differences between pixel values of each frame and a previous frame are taken as input covariates for applying the regression model to the activity probability, wherein the integrating comprises quantifying the accuracy probability of each of the plurality of human detection modalities within each frame and selecting a human detection modality among the plurality of human detection modalities with maximum accuracy probability above the integrated fusion characteristic results; and counting humans in each frame using the selected human detection modality.