An empirical study of context in object detection

This paper presents an empirical evaluation of the role of context in a contemporary, challenging object detection task - the PASCAL VOC 2008. Previous experiments with context have mostly been done on home-grown datasets, often with non-standard baselines, making it difficult to isolate the contribution of contextual information. In this work, we present our analysis on a standard dataset, using top-performing local appearance detectors as baseline. We evaluate several different sources of context and ways to utilize it. While we employ many contextual cues that have been used before, we also propose a few novel ones including the use of geographic context and a new approach for using object spatial support.

[1]  Thomas M. Strat,et al.  Employing Contextual Information in Computer Vision , 1993 .

[2]  Thorsten Joachims,et al.  Making large scale SVM learning practical , 1998 .

[3]  Nello Cristianini,et al.  Advances in Kernel Methods - Support Vector Learning , 1999 .

[4]  Olga Veksler,et al.  Fast Approximate Energy Minimization via Graph Cuts , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Antonio Torralba,et al.  Statistical Context Priming for Object Detection , 2001, ICCV.

[6]  Jiebo Luo,et al.  Probabilistic spatial context models for scene content understanding , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[7]  Antonio Torralba,et al.  Statistics of natural image categories , 2003, Network.

[8]  Antonio Torralba,et al.  Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes , 2003, NIPS.

[9]  Yee Whye Teh,et al.  Names and faces in the news , 2004, CVPR 2004.

[10]  Nando de Freitas,et al.  A Statistical Model for General Contextual Object Recognition , 2004, ECCV.

[11]  Andrew Zisserman,et al.  A Statistical Approach to Texture Classification from Single Images , 2004, International Journal of Computer Vision.

[12]  Antonio Torralba,et al.  Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.

[13]  Antonio Torralba,et al.  Contextual Priming for Object Detection , 2003, International Journal of Computer Vision.

[14]  Shree K. Nayar,et al.  Vision and the Atmosphere , 2002, International Journal of Computer Vision.

[15]  Pietro Perona,et al.  A Bayesian hierarchical model for learning natural scene categories , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[16]  Martial Hebert,et al.  A hierarchical field framework for unified context-based classification , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[17]  Christopher K. I. Williams,et al.  Pascal Visual Object Classes Challenge Results , 2005 .

[18]  Alexei A. Efros,et al.  Geometric context from a single image , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[19]  J. McGregor.  Context , 2018, J. Object Technol..

[20]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[21]  Jianguo Zhang,et al.  The PASCAL Visual Object Classes Challenge , 2006 .

[22]  Alexei A. Efros,et al.  Recovering Surface Layout from an Image , 2007, International Journal of Computer Vision.

[23]  Antonio Torralba,et al.  Building the gist of a scene: the role of global image features in recognition. , 2006, Progress in brain research.

[24]  Lior Wolf,et al.  A Critical View of Context , 2006, International Journal of Computer Vision.

[25]  Jiebo Luo,et al.  Pictures Are Not Taken in a Vacuum , 2006 .

[26]  Alexei A. Efros,et al.  Putting Objects in Perspective , 2006, CVPR.

[27]  Cordelia Schmid,et al.  Dataset Issues in Object Recognition , 2006, Toward Category-Level Object Recognition.

[28]  Antonio Criminisi,et al.  TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation , 2006, ECCV.

[29]  Deva Ramanan,et al.  Using Segmentation to Verify Object Hypotheses , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[30]  Antonio Torralba,et al.  LabelMe: A Database and Web-Based Tool for Image Annotation , 2008, International Journal of Computer Vision.

[31]  Antonio Torralba,et al.  Object Recognition by Scene Alignment , 2007, NIPS.

[32]  BoydStephen,et al.  An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression , 2007 .

[33]  Alexei A. Efros,et al.  Recovering Occlusion Boundaries from a Single Image , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[34]  Andrea Vedaldi,et al.  Objects in Context , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[35]  Alexei A. Efros,et al.  Photo clip art , 2007, ACM Trans. Graph..

[36]  A. Torralba,et al.  The role of context in object recognition , 2007, Trends in Cognitive Sciences.

[37]  Daphne Koller,et al.  Learning Spatial Context: Using Stuff to Find Things , 2008, ECCV.

[38]  Alexei A. Efros,et al.  What Does the Sky Tell Us about the Camera? , 2008, ECCV.

[39]  Jitendra Malik,et al.  Using contours to detect and localize junctions in natural images , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[40]  Steven M. Seitz,et al.  Scene Segmentation Using the Wisdom of Crowds , 2008, ECCV.

[41]  David A. McAllester,et al.  A discriminatively trained, multiscale, deformable part model , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[42]  Tsuhan Chen,et al.  Estimating age, gender, and identity using first name priors , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[43]  Larry S. Davis,et al.  Beyond Nouns: Exploiting Prepositions and Comparative Adjectives for Learning Visual Classifiers , 2008, ECCV.

[44]  Antonio Torralba,et al.  SIFT Flow: Dense Correspondence across Different Scenes , 2008, ECCV.

[45]  Alexei A. Efros,et al.  IM2GPS: estimating geographic information from a single image , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[46]  Serge J. Belongie,et al.  Object categorization using co-occurrence, location and appearance , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[47]  Carman Neustaedter,et al.  Image annotation using personal calendars as context , 2008, ACM Multimedia.

[48]  Serge J. Belongie,et al.  Context based object categorization: A critical survey , 2010, Comput. Vis. Image Underst..