Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Advances in kernel methods: support vector learning
Advances in kernel methods: support vector learning
Image classification and querying using composite region templates
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Segmentation by Data-Driven Markov Chain Monte Carlo
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Content-Based Ima e Orientation Detection with Support Vector Machines
CBAIVL '01 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'01)
A statistical approach to 3d object detection applied to faces and cars
A statistical approach to 3d object detection applied to faces and cars
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Probabilistic spatial context models for scene content understanding
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A physical model-based approach to detecting sky in photographic images
IEEE Transactions on Image Processing
Automatic image orientation detection
IEEE Transactions on Image Processing
Detector of image orientation based on Borda Count
Pattern Recognition Letters
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Upright orientation of man-made objects
ACM SIGGRAPH 2008 papers
Mining GPS traces and visual words for event classification
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
What's up CAPTCHA?: a CAPTCHA based on image orientation
Proceedings of the 18th international conference on World wide web
Motion estimation by decoupling rotation and translation in catadioptric vision
Computer Vision and Image Understanding
Sketcha: a captcha based on line drawings of 3D models
Proceedings of the 19th international conference on World wide web
Text-based video content classification for online video-sharing sites
Journal of the American Society for Information Science and Technology
Study of storage yard PRIC key technologies based on modern measurement and control
IMCAS'06 Proceedings of the 5th WSEAS international conference on Instrumentation, measurement, circuits and systems
Musical slideshow: boosting user experience in photo presentation
Multimedia Tools and Applications
An algorithm for the automatic estimation of image orientation
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
| Hi-index | 0.14 |
Automatic image orientation detection for natural images is a useful, yet challenging research topic. Humans use scene context and semantic object recognition to identify the correct image orientation. However, it is difficult for a computer to perform the task in the same way because current object recognition algorithms are extremely limited in their scope and robustness. As a result, existing orientation detection methods were built upon low-level vision features such as spatial distributions of color and texture. Discrepant detection rates have been reported for these methods in the literature. We have developed a probabilistic approach to image orientation detection via confidence-based integration of low-level and semantic cues within a Bayesian framework. Our current accuracy is 90 percent for unconstrained consumer photos, impressive given the findings of a psychophysical study conducted recently. The proposed framework is an attempt to bridge the gap between computer and human vision systems and is applicable to other problems involving semantic scene content understanding.