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New Object Detection for On-board Robot Vision by Lifting Complex Wavelet Transforms

Shigeru Takano, Einoshin Suzuki

Year
2011
Citations
6

Abstract

This paper aims to develop a fast algorithm for detecting a new object from video sequences captured by on-board robot vision. We first propose lifting complex wavelet, which is a new method for extracting local features in an image. The proposed lifting complex wavelet transforms can be detected the features faster than the conventional SIFT algorithm. Our new object detection is performed by using an overlap ratio between the local features of current- and past-frames. In experiments, we show that new objects can be detected fast from on-board robot vision.

Keywords

Artificial intelligenceComputer visionComputer scienceWaveletObject detectionWavelet transformRobotScale-invariant feature transformObject (grammar)Lifting scheme

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