  In order to understand content and automatically extract labels for videos of
the game "Honor of Kings", it is necessary to detect and recognize characters
(called "hero") together with their camps in the game video. In this paper, we
propose an efficient two-stage algorithm to detect and recognize heros in game
videos. First, we detect all heros in a video frame based on blood bar
template-matching method, and classify them according to their camps (self/
friend/ enemy). Then we recognize the name of each hero using one or more deep
convolution neural networks. Our method needs almost no work for labelling
training and testing samples in the recognition stage. Experiments show its
efficiency and accuracy in the task of hero detection and recognition in game
videos.
