论文标题
语义图像搜索机器人应用
Semantic Image Search for Robotic Applications
论文作者
论文摘要
机器人技术的概括是最重要的问题之一。新的概括方法使用Internet数据库来解决新任务。现代搜索引擎可以根据毫秒内的查询返回大量信息。但是，并非所有返回的信息都与任务相关，部分是由于多理化的问题。在这里，我们通过使用图像搜索专门解决了对象概括的问题。我们建议一个基于人类使用其他语言提示来划定预期的单词含义的观察结果，将视觉和文本信息结合在一起。我们通过将方法与人类标记的数据进行比较来评估我们的方法的质量，并发现与Google搜索相比，我们的方法平均可以改善结果，并且可以治疗多聚合物的问题。
Generalization in robotics is one of the most important problems. New generalization approaches use internet databases in order to solve new tasks. Modern search engines can return a large amount of information according to a query within milliseconds. However, not all of the returned information is task relevant, partly due to the problem of polysemes. Here we specifically address the problem of object generalization by using image search. We suggest a bi-modal solution, combining visual and textual information, based on the observation that humans use additional linguistic cues to demarcate intended word meaning. We evaluate the quality of our approach by comparing it to human labelled data and find that, on average, our approach leads to improved results in comparison to Google searches, and that it can treat the problem of polysemes.
