A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Precision Edge Contrast and Orientation Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Sensitivity of the Hough Transform for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Recognizing and Positioning Curved 3-D Objects from Image Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic approach to the Hough transform
Image and Vision Computing
A probability weighted Hough transform technique for shape retrieval from noisy imagery
Pattern Recognition Letters
3D free-form object recognition using indexing by contour features
Computer Vision and Image Understanding
A survey of free-form object representation and recognition techniques
Computer Vision and Image Understanding
3D Object recognition in cluttered environments by segment-based stereo vision
International Journal of Computer Vision
Silhouette-Based Isolated Object Recognition through Curvature Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Class-Specific, Top-Down Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Hierarchical Recognition of Articulated Objects from Single Perspective Views
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Recognition by Linear Combination of Models
Recognition by Linear Combination of Models
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
| Hi-index | 0.11 |
We present a method to detect the seat and head-rest of the by-passenger, as a part of a smart airbag system. The recognition of the seat and head-rest is useful for the purpose of background subtraction, as well as for assisting head-tracking and occupant classification. We use a multi-resolution probabilistic generalized Hough transform (GHT). We present experimental results for the detection, as well as an error analysis. Our experiments were performed using an imperfect set of models on close-range images with low dynamic range and under sever occlusions. Nevertheless, we have found that one needs to consider only the best 11 hypotheses of the GHT to ensure recognition. Moreover, when at least 25% of the seat contour is not occluded, only two hypotheses are needed on the average. The results show that the head-rest is a more robust clue than the seat. Finally, we discuss how to extend our work and possible uses in the context of occupant detection and classification.