Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Experiences with an interactive museum tour-guide robot
Artificial Intelligence - Special issue on applications of artificial intelligence
A Trainable System for Object Detection
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Jijo-2: An Office Robot that Communicates and Learns
IEEE Intelligent Systems
Multi-view Matching for Unordered Image Sets, or "How Do I Organize My Holiday Snaps?"
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Summed-area tables for texture mapping
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Detecting Pedestrians Using Patterns of Motion and Appearance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Providing the basis for human-robot-interaction: a multi-modal attention system for a mobile robot
Proceedings of the 5th international conference on Multimodal interfaces
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
People detection and tracking using stereo vision and color
Image and Vision Computing
Stereovision-based object segmentation for automotive applications
EURASIP Journal on Applied Signal Processing
Robotics and Autonomous Systems
Stereo- and neural network-based pedestrian detection
IEEE Transactions on Intelligent Transportation Systems
Pedestrian Protection Systems: Issues, Survey, and Challenges
IEEE Transactions on Intelligent Transportation Systems
Combining content-based analysis and crowdsourcing to improve user interaction with zoomable video
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Indoor Mobile Robotics at Grima, PUC
Journal of Intelligent and Robotic Systems
Indoor scene recognition by a mobile robot through adaptive object detection
Robotics and Autonomous Systems
Saliency detection based on integrated features
Neurocomputing
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Human detection is a key ability to an increasing number of applications that operates in human inhabited environments or needs to interact with a human user. Currently, most successful approaches to human detection are based on background substraction techniques that apply only to the case of static cameras or cameras with highly constrained motions. Furthermore, many applications rely on features derived from specific human poses, such as systems based on features derived from the human face which is only visible when a person is facing the detecting camera. In this work, we present a new computer vision algorithm designed to operate with moving cameras and to detect humans in different poses under partial or complete view of the human body. We follow a standard pattern recognition approach based on four main steps: (i) preprocessing to achieve color constancy and stereo pair calibration, (ii) segmentation using depth continuity information, (iii) feature extraction based on visual saliency, and (iv) classification using a neural network. The main novelty of our approach lies in the feature extraction step, where we propose novel features derived from a visual saliency mechanism. In contrast to previous works, we do not use a pyramidal decomposition to run the saliency algorithm, but we implement this at the original image resolution using the so-called integral image. Our results indicate that our method: (i) outperforms state-of-the-art techniques for human detection based on face detectors, (ii) outperforms state-of-the-art techniques for complete human body detection based on different set of visual features, and (iii) operates in real time onboard a mobile platform, such as a mobile robot (15fps).