Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modelling binocular neurons in the primary visual cortex
Computational and psychophysical mechanisms of visual coding
Information Retrieval
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Statistical Learning of Multi-view Face Detection
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Rotation Invariant Neural Network-Based Face Detection
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Robust Real-Time Face Detection
International Journal of Computer Vision
Bayesian face recognition using Gabor features
WBMA '03 Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications
Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Synergistic Face Detection and Pose Estimation with Energy-Based Models
The Journal of Machine Learning Research
Robust Object Recognition with Cortex-Like Mechanisms
IEEE Transactions on Pattern Analysis and Machine Intelligence
High-Performance Rotation Invariant Multiview Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computing stereo disparity and motion with known binocular cell properties
Neural Computation
Face detection using simplified Gabor features and hierarchical regions in a cascade of classifiers
Pattern Recognition Letters
Face detection and tracking in video sequences using the modifiedcensus transformation
Image and Vision Computing
Image and Vision Computing
Robust face detection using Gabor filter features
Pattern Recognition Letters
Fast rotation invariant multi-view face detection based on real adaboost
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Using depth information to improve face detection
Proceedings of the 6th international conference on Human-robot interaction
Face detection using convolutional neural networks and gabor filters
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Novel face detection method based on gabor features
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Enhancing Human Face Detection by Resampling Examples Through Manifolds
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Intuitively, integrating information from multiple visual cues, such as texture, stereo disparity, and image motion, should improve performance on perceptual tasks, such as object detection. On the other hand, the additional effort required to extract and represent information from additional cues may increase computational complexity. In this work, we show that using biologically inspired integrated representation of texture and stereo disparity information for a multi-view facial detection task leads to not only improved detection performance, but also reduced computational complexity. Disparity information enables us to filter out 90% of image locations as being less likely to contain faces. Performance is improved because the filtering rejects 32% of the false detections made by a similar monocular detector at the same recall rate. Despite the additional computation required to compute disparity information, our binocular detector takes only 42ms to process a pair of 640x480 images, 35% of the time required by the monocular detector. We also show that this integrated detector is computationally more efficient than a detector with similar performance where texture and stereo information is processed separately.