Learning to Count with CNN Boosting [chapter]

Elad Walach, Lior Wolf
2016 Lecture Notes in Computer Science  
In this paper, we address the task of object counting in images. We follow modern learning approaches in which a density map is estimated directly from the input image. We employ CNNs and incorporate two significant improvements to the state of the art methods: layered boosting and selective sampling. As a result, we manage both to increase the counting accuracy and to reduce processing time. Moreover, we show that the proposed method is effective, even in the presence of labeling errors.
more » ... ive experiments on five different datasets demonstrate the efficacy and robustness of our approach. Mean Absolute error was reduced by 20% to 35%. At the same time, the training time of each CNN has been reduced by 50%.
doi:10.1007/978-3-319-46475-6_41 fatcat:d74atjc4yjgbphwtf42vxwj4j4