Pose invariant generic object recognition with orthogonal axis manifolds in linear subspace

Authors:
Manisha Kalra;P. Deepti;R. Abhilash;Sukhendu Das
Affiliations:
Visualization and Perception Laboratory, Department of Computer Science and Engineering, Indian Institute of Technology – Madras, Chennai, India;Visualization and Perception Laboratory, Department of Computer Science and Engineering, Indian Institute of Technology – Madras, Chennai, India;Visualization and Perception Laboratory, Department of Computer Science and Engineering, Indian Institute of Technology – Madras, Chennai, India;Visualization and Perception Laboratory, Department of Computer Science and Engineering, Indian Institute of Technology – Madras, Chennai, India
Venue:
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Year:
2006

Citing 11
Cited 0

Visual learning and recognition of 3-D objects from appearance

International Journal of Computer Vision
On Combining Classifiers

IEEE Transactions on Pattern Analysis and Machine Intelligence
Support Vector Machines for 3D Object Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust recognition using eigenimages

Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
Shape Matching and Object Recognition Using Shape Contexts

IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
"GrabCut": interactive foreground extraction using iterated graph cuts

ACM SIGGRAPH 2004 Papers
3D Object Modeling and Recognition Using Local Affine-Invariant Image Descriptors and Multi-View Spatial Constraints

International Journal of Computer Vision
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Rapid and brief communication: Visual learning and recognition of 3D objects using two-dimensional principal component analysis: A robust and an efficient approach

Pattern Recognition
Fast and robust fixed-point algorithms for independent component analysis

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper addresses the problem of pose invariant Generic Object Recognition by modeling the perceptual capability of human beings. We propose a novel framework using a combination of appearance and shape cues to recognize the object class and viewpoint (axis of rotation) as well as determine its pose (angle of view). The appearance model of the object from multiple viewpoints is captured using Linear Subspace Analysis techniques and is used to reduce the search space to a few rank-ordered candidates. We have used a decision-fusion based combination of 2D PCA and ICA to integrate the complementary information of classifiers and improve recognition accuracy. For matching based on shape features, we propose the use of distance transform based correlation. A decision fusion using ‘Sum Rule' of 2D PCA and ICA subspace classifiers, and distance transform based correlation is then used to verify the correct object class and determine its viewpoint and pose. Experiments were conducted on COIL-100 and IGOIL (IITM Generic Object Image Library) databases which contain objects with complex appearance and shape characteristics. IGOIL database was captured to analyze the appearance manifolds along two orthogonal axes of rotation.