  Social event detection in a static image is a very challenging problem and
it's very useful for internet of things applications including automatic photo
organization, ads recommender system, or image captioning. Several publications
show that variety of objects, scene, and people can be very ambiguous for the
system to decide the event that occurs in the image. We proposed the spatial
pyramid configuration of convolutional neural network (CNN) classifier for
social event detection in a static image. By applying the spatial pyramid
configuration to the CNN classifier, the detail that occurs in the image can
observe more accurately by the classifier. USED dataset provided by Ahmad et
al. is used to evaluate our proposed method, which consists of two different
image sets, EiMM, and SED dataset. As a result, the average accuracy of our
system outperforms the baseline method by 15% and 2% respectively.
