Probabilistic Model of Object Detection Based on Convolutional Neural Network

2018/08/16 by Fang-Qi Li, Li, Fang-Qi, Xu-Die Ren +3
Computer Science · Mathematics · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.CV #cs.LG #stat.ML

paper · pdf · doi:10.48550/arxiv.1808.08272

8 pages, 8 figures, International Conference on Communication, Signal Processing and Systems (CSPS 2017)

arxiv created 2018/08/16 · arxiv updated 2018/08/28

Abstract

The combination of a CNN detector and a search framework forms the basis for local object/pattern detection. To handle the waste of regional information and the defective compromise between efficiency and accuracy, this paper proposes a probabilistic model with a powerful search framework. By mapping an image into a probabilistic distribution of objects, this new model gives more informative outputs with less computation. The setting and analytic traits are elaborated in this paper, followed by a series of experiments carried out on FDDB, which show that the proposed model is sound, efficient and analytic.

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