A Pedestrian-Detection Method Based on Heterogeneous Features and Ensemble of Multi-View–Pose Parts
- 28 August 2014
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Intelligent Transportation Systems
- Vol. 16 (15249050), 1-12
- https://doi.org/10.1109/tits.2014.2342936
Abstract
Vision-based pedestrian detection remains a challenging task, so far. The detection performance often suffers from the various appearances of pedestrians, the illumination changes, and the possible partial occlusions. Aiming at resolving these challenges, in this paper, a new linear kernel function is proposed to effectively combine two heterogeneous features, i.e., histogram of oriented gradient and local binary pattern, which enhances the pedestrian description ability to illumination conditions and cluttered background. Then, a novel multi-view-pose part ensemble (MVPPE) detector is proposed, in order to better handle pedestrian variability, views, and partial occlusions. Experimental results in public data sets demonstrate that the proposed feature combination method significantly improves the description capabilities of pedestrian features. Compared with the existing multipart ensemble approaches, the proposed MVPPE detector boosts higher detection accuracy.Keywords
Funding Information
- National Natural Science Foundation of China (61273239)
- Fundamental Research Funds for the Central Universities of China (120418001)
This publication has 37 references indexed in Scilit:
- Learning a multiview part-based model in virtual world for pedestrian detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- Different Region Analysis for Genotyping Yersinia pestis Isolates from ChinaPLOS ONE, 2008
- Haar Wavelets and Edge Orientation Histograms for On–Board Pedestrian DetectionLecture Notes in Computer Science, 2007
- The Treelike Assembly Classifier for Pedestrian DetectionLecture Notes in Computer Science, 2007
- A Review on Vision-Based Pedestrian Detection for Intelligent VehiclesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Detecting Pedestrians Using Patterns of Motion and AppearanceInternational Journal of Computer Vision, 2005
- Robust Real-Time Face DetectionInternational Journal of Computer Vision, 2004
- Multiresolution gray-scale and rotation invariant texture classification with local binary patternsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
- Example-based object detection in images by componentsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2001
- A Global Geometric Framework for Nonlinear Dimensionality ReductionScience, 2000