Camcorder operation judgment using a neural computing approach

In this study, the neural computing approach as applied to the judgment of the camcorder operations which include fix-shot, panning and tilting. The data used in this study is the moving vector obtained from the real camcorder image. Also, seven features are carefully selected as possible inputs to this neural network. As a result of this approach, 96.88% accuracy of the operation judgment is obtained by using the length, angle of the moving vector and the time variation of the moving vector length as a set of three features. This result indicates that the approach proposed here can indeed classify three classes in the camcorder operations and it is also very easy to be utilized to control the automatic functions in the camcorder as well