Probabilistic Modeling and Recognition of 3-D Objects
International Journal of Computer Vision
Information Theoretic Sensor Data Selection for Active Object Recognition and State Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Optimal Camera Parameter Selection in Kalman Filter Based Object Tracking
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Optimal Camera Parameter Selection for State Estimation with Applications in Object Recognition
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
On Fusion of Multiple Views for Active Object Recognition
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
Efficient Discriminant Viewpoint Selection for Active Bayesian Recognition
International Journal of Computer Vision
Comparing active vision models
Image and Vision Computing
Context based object detection from video
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
Aspects of optimal viewpoint selection and viewpoint fusion
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Information-gain view planning for free-form object reconstruction with a 3d ToF camera
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
A Computational Learning Theory of Active Object Recognition Under Uncertainty
International Journal of Computer Vision
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This article develops an analogy between object recognition and the transmission of information through a channel based on the statistical representation of the appearances of 3D objects. This analogy provides a means to quantitatively evaluate the contribution of individual receptive field vectors, and to predict the performance of the object recognition process. Transinformation also provides a quantitative measure of the discrimination provided by each viewpoint, thus permitting the determination of the most discriminant viewpoints. As an application, the article develops an active object recognition algorithm which is able to resolve ambiguities inherent in a single-view recognition algorithm.