  Deep neural network based learning approaches is widely utilized for image
classification or object detection based problems with remarkable outcomes.
Realtime Object state estimation of objects can be used to track and estimate
the features that the object of the current frame possesses without causing any
significant delay and misclassification. A system that can detect the features
of such objects in the present state from camera images can be used to enhance
the application of Augmented Reality for improving user experience and
delivering information in a much perceptual way. The focus behind this paper is
to determine the most suitable model to create a low-latency assistance AR to
aid users by providing them nutritional information about the food that they
consume in order to promote healthier life choices. Hence the dataset has been
collected and acquired in such a manner, and we conduct various tests in order
to identify the most suitable DNN in terms of performance and complexity and
establish a system that renders such information realtime to the user.
