基於深度學習技術之行人年齡與性別辨識

Age and Gender Recognition of Full Body Pedestrian Images Based on Deep Learning

張家豪(Chia-Hao Chang)

指導教授 ： 王才沛

國立交通大學/資訊學院/資訊科學與工程研究所/碩士(2018年)

摘要

本論文研究目標為利用深度學習技術實作人物影像之年齡與性別的辨識，主要研究對象為街道上行人的全身影像，擷取出單一行人之全身影像，進行辨識後得出其年齡性別之辨識結果。
基於深度學習(Deep Learning)技術，我們使用卷積神經網路(CNN)作為網路主架構提取特徵(feature)，並提供年齡與性別之分類器共享特徵來優化特徵提取過程，最後評估各式實驗間的差異，彙整成我們的結論。

關鍵字

全身人物影像性別辨識 ； 全身人物影像年齡辨識

並列摘要

The research goal is to implement a deep learning model for age and gender recognition. The main object of study is the full body images of pedestrian. After cropping the full body image of each pedestrian in the frame, these pedestrian images are inferenced their recognition results.
Based on deep learning model, we use convolution neural network as our backbone of the network to extract features, and provide age and gender classifier sharing features to optimize the feature extraction process. Finally, we evaluate the differences between all experiments in this paper and integrate them into our conclusions.

並列關鍵字

Gender Recognition of Full Body ； Age Recognition of Full Body

參考文獻

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