Optical flow from 1-D correlation: application to a simple time-to-crash detector
International Journal of Computer Vision - Special issue on qualitative vision
Vanishing Point Detection by Line Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Symmetry as a Continuous Feature
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Framework for Variable -Resolution Vision
ICCI '91 Proceedings of the International Conference on Computing and Information: Advances in Computing and Information
Visual Correspondence Using Energy Minimization and Mutual Information
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Robust Real-Time Face Detection
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
IEEE Transactions on Computers
Stereo Processing by Semiglobal Matching and Mutual Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient training of artificial neural networks for autonomous navigation
Neural Computation
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
General road detection from a single image
IEEE Transactions on Image Processing
Polly: a vision-based artificial agent
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Detecting faces from low-resolution images
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Low-resolution vision for autonomous mobile robots
Low-resolution vision for autonomous mobile robots
Extracting minimalistic corridor geometry from low-resolution images
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
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We present a technique for mobile robot exploration in unknown indoor environments using only a single forward-facing camera. Rather than processing all the data, the method intermittently examines only small 32脳24 downsampled grayscale images. We show that for the task of indoor exploration the visual information is highly redundant, allowing successful navigation even using only a small fraction of the available data. The method keeps the robot centered in the corridor by estimating two state parameters: the orientation within the corridor, and the distance to the end of the corridor. The orientation is determined by combining the results of five complementary measures, while the estimated distance to the end combines the results of three complementary measures. These measures, which are predominantly information-theoretic, are analyzed independently, and the combined system is tested in several unknown corridor buildings exhibiting a wide variety of appearances, showing the sufficiency of low-resolution visual information for mobile robot exploration. Because the algorithm discards such a large percentage of the pixels both spatially and temporally, processing occurs at an average of 1000 frames per second, thus freeing the processor for other concurrent tasks.