Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons
International Journal of Computer Vision
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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
A Hierarchical Field Framework for Unified Context-Based Classification
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Large-Scale Concept Ontology for Multimedia
IEEE MultiMedia
An Experimental Study on Pedestrian Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 15th international conference on Multimedia
Leveraging probabilistic season and location context models for scene understanding
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
What Does the Sky Tell Us about the Camera?
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Proceedings of the 18th international conference on World wide web
CrowdReranking: exploring multiple search engines for visual search reranking
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Context based object categorization: A critical survey
Computer Vision and Image Understanding
Co-reranking by mutual reinforcement for image search
Proceedings of the ACM International Conference on Image and Video Retrieval
Survey of Pedestrian Detection for Advanced Driver Assistance Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Context-based friend suggestion in online photo-sharing community
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Typicality-Based Visual Search Reranking
IEEE Transactions on Circuits and Systems for Video Technology
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Most existing approaches to pedestrian detection only use the visual appearances as the main source in real world images. However, the visual information cannot always provide reliable guidance since pedestrians often change pose or wear different clothes under different conditions. In this work, by leveraging a vast amount of Web images, we first construct a contextual image database, in which each image is automatically attached with geographic location (i.e., latitude and longitude) and environment information (i.e., season, time and weather condition), assisted by image metadata and a few pre-trained classifiers. For the further pedestrian detection, an annotation scheme is presented which can sharply decrease manual labeling efforts. Several properties of the contextual image database are studied including whether the database is authentic and helpful for pedestrian detection. Moreover, we propose a context-based pedestrian detection approach by jointly exploring visual and contextual cues in a probabilistic model. Encouraging results are reported on our contextual image database.