IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
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
Group Theoretical Structure of Spectral Spaces
Journal of Mathematical Imaging and Vision
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
International Journal of Computer Vision
Scene Classification Using a Hybrid Generative/Discriminative Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning color names for real-world applications
IEEE Transactions on Image Processing
The Pascal Visual Object Classes (VOC) Challenge
International Journal of Computer Vision
Evaluating Color Descriptors for Object and Scene Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discriminative Video Pattern Search for Efficient Action Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
On importance of interactions and context in human action recognition: Nataliya,,Shapovalova
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Discriminative compact pyramids for object and scene recognition
Pattern Recognition
Weakly Supervised Learning of Interactions between Humans and Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coloring local feature extraction
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Double fusion for multimedia event detection
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
Action recognition from a distributed representation of pose and appearance
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Actom sequence models for efficient action detection
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Modulating Shape Features by Color Attention for Object Recognition
International Journal of Computer Vision
Color attributes for object detection
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Discriminative spatial saliency for image classification
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Human action recognition by learning bases of action attributes and parts
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Diagnosing error in object detectors
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Detecting actions, poses, and objects with relational phraselets
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Expanded Parts Model for Human Attribute and Action Recognition in Still Images
CVPR '13 Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition
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In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color---shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification.