Human Detection Based on a Probabilistic Assembly of Robust Part Detectors

We describe a novel method for human detection in single images which can detect full bodies as well as close-up views in the presence of clutter and occlusion. Humans are modeled as flexible assemblies of parts, and robust part detection is the key to the approach. The parts are represented by co-occurrences of local features which captures the spatial layout of the partrsquos appearance. Feature selection and the part detectors are learnt from training images using AdaBoost. The detection algorithm is very efficient as (i) all part detectors use the same initial features, (ii) a coarse-to-fine cascade approach is used for part detection, (iii) a part assembly strategy reduces the number of spurious detections and the search space. The results outperform existing human detectors.

[1]  David A. Forsyth,et al.  Body plans , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[2]  Yoram Singer,et al.  Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.

[3]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[4]  Takeo Kanade,et al.  A statistical method for 3D object detection applied to faces and cars , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[5]  Daniel P. Huttenlocher,et al.  Efficient matching of pictorial structures , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[6]  Dariu Gavrila,et al.  Pedestrian Detection from a Moving Vehicle , 2000, ECCV.

[7]  Christopher M. Bishop,et al.  Non-linear Bayesian Image Modelling , 2000, ECCV.

[8]  Pedro F. Felzenszwalb.  Learning models for object recognition , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[9]  Michael J. Black,et al.  Learning image statistics for Bayesian tracking , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[10]  Tomaso A. Poggio,et al.  Example-Based Object Detection in Images by Components , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Cordelia Schmid,et al.  Face detection in a video sequence - a temporal approach , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[12]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[13]  Harry Shum,et al.  Statistical Learning of Multi-view Face Detection , 2002, ECCV.

[14]  Mads Nielsen,et al.  Computer Vision — ECCV 2002 , 2002, Lecture Notes in Computer Science.

[15]  Cordelia Schmid,et al.  Learning to Parse Pictures of People , 2002, ECCV.

[16]  Michael Isard,et al.  Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief Propagation , 2003, NIPS.

[17]  Bernt Schiele,et al.  Using Local Context To Improve Face Detection , 2003, BMVC.

[18]  Pietro Perona,et al.  Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[19]  David A. Forsyth,et al.  Finding and tracking people from the bottom up , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[20]  Henry Schneiderman,et al.  Learning Statistical Structure for Object Detection , 2003, CAIP.

[21]  Cheng Lu,et al.  Intrinsic Images by Entropy Minimization , 2004, ECCV.

[22]  Carlo Tomasi,et al.  Image Similarity Using Mutual Information of Regions , 2004, ECCV.

[23]  Narendra Ahuja,et al.  A Robust Probabilistic Estimation Framework for Parametric Image Models , 2004, ECCV.

[24]  Stefano Soatto,et al.  Spatially Homogeneous Dynamic Textures , 2004, ECCV.

[25]  Timothy F. Cootes,et al.  Groupwise Diffeomorphic Non-rigid Registration for Automatic Model Building , 2004, ECCV.

[26]  David A. Forsyth,et al.  Probabilistic Methods for Finding People , 2001, International Journal of Computer Vision.

[27]  Fabrice Heitz,et al.  A Topology Preserving Non-rigid Registration Method Using a Symmetric Similarity Function-Application to 3-D Brain Images , 2004, ECCV.

[28]  Pierre Charbonnier,et al.  Evaluation of Robust Fitting Based Detection , 2004, ECCV.

[29]  Andrew Zisserman,et al.  An Affine Invariant Salient Region Detector , 2004, ECCV.

[30]  Bo Thiesson,et al.  Image and Video Segmentation by Anisotropic Kernel Mean Shift , 2004, ECCV.

[31]  Daniel Cremers,et al.  Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation , 2004, ECCV.

[32]  Pietro Perona,et al.  A Visual Category Filter for Google Images , 2004, ECCV.

[33]  Thomas Brox,et al.  High Accuracy Optical Flow Estimation Based on a Theory for Warping , 2004, ECCV.

[34]  Aaron Hertzmann,et al.  Automatic Non-rigid 3D Modeling from Video , 2004, ECCV.

[35]  Stefan Carlsson,et al.  Appearance Based Qualitative Image Description for Object Class Recognition , 2004, ECCV.

[36]  Harry Shum,et al.  Synthesizing Dynamic Texture with Closed-Loop Linear Dynamic System , 2004, ECCV.

[37]  Patrick Pérez,et al.  Interactive Image Segmentation Using an Adaptive GMMRF Model , 2004, ECCV.

[38]  Tomaso A. Poggio,et al.  A Trainable System for Object Detection , 2000, International Journal of Computer Vision.

[39]  Pascal Fua,et al.  Texture Boundary Detection for Real-Time Tracking , 2004, ECCV.

[40]  Jing Xiao,et al.  A Closed-Form Solution to Non-Rigid Shape and Motion Recovery , 2004, International Journal of Computer Vision.

[41]  Cordelia Schmid,et al.  A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[42]  Andrew Zisserman,et al.  Object Level Grouping for Video Shots , 2004, International Journal of Computer Vision.

[43]  Tony Lindeberg,et al.  Detecting salient blob-like image structures and their scales with a scale-space primal sketch: A method for focus-of-attention , 1993, International Journal of Computer Vision.

[44]  Luc Van Gool,et al.  Edinburgh Research Explorer Simultaneous Object Recognition and Segmentation by Image Exploration , 2022 .