Multi-camera object detection for robotics

13 years 2 months ago

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— Robust object detection is a critical skill for robotic applications in complex environments like homes and ofﬁces. In this paper we propose a method for using multiple cameras to simultaneously view an object from multiple angles and at high resolutions. We show that our probabilistic method for combining the camera views, which can be used with many choices of single-image object detector, can signiﬁcantly improve accuracy for detecting objects from many viewpoints. We also present our own single-image object detection method that uses large synthetic datasets for training. Using a distributed, parallel learning algorithm, we train from very large datasets (up to 100 million image patches). The resulting object detector achieves high performance on its own, but also beneﬁts substantially from using multiple camera views. Our experimental results validate our system in realistic conditions and demonstrates signiﬁcant performance gains over using standard single-image class...

Adam Coates, Andrew Y. Ng

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