论文标题
将小苹果定位在复杂的苹果园环境中
Localizing Small Apples in Complex Apple Orchard Environments
论文作者
论文摘要
水果的定位是自动化农业管道的重要第一步，用于收益估算或取果。一个例子是在整个苹果树的图像中定位苹果。由于在这种情况下，苹果是很小的对象，因此我们通过调整专注于小物体的对象提案的生成系统注意措施来解决此问题。我们通过添加一个非常小的苹果的新模块或将其集成到平铺框架中来调整注意事项。两种方法都显然超过了涵盖复杂苹果园环境的Minneapple数据集上的标准对象提案系统。我们的评估进一步分析了W.R.T.的改进苹果尺寸并显示了我们两种方法的不同特征。
The localization of fruits is an essential first step in automated agricultural pipelines for yield estimation or fruit picking. One example of this is the localization of apples in images of entire apple trees. Since the apples are very small objects in such scenarios, we tackle this problem by adapting the object proposal generation system AttentionMask that focuses on small objects. We adapt AttentionMask by either adding a new module for very small apples or integrating it into a tiling framework. Both approaches clearly outperform standard object proposal generation systems on the MinneApple dataset covering complex apple orchard environments. Our evaluation further analyses the improvement w.r.t. the apple sizes and shows the different characteristics of our two approaches.
