This research is mainly based on automating the process of calculating the time taken for any actor to appear on the screen. It is one of the main factors for determining the remuneration to be given to actors for appearing on the screen for a particular time period. By automating this process, we can accurately determine the screen time of an actor with minimum error. This proposed idea can be implemented using the knowledge related to image processing with the help of CNN architecture. The major part of the research lies in determining the hyperparameters and the right model that fits the given video appropriately and gives the best results for the model evaluation. The major findings of this paper lie on analyzing the right activation function, the number of layers for the neural network, finding the drop-out rate for the trained neural network, deciding upon the weight sharing of the input attributes, and of the hidden layers. The final outcome of this performed experiment is a neural network that can be used for deciding the duration of an actor on the screen.