K. Toyama and G. Hager. Incremental focus of attention for robust vision-based tracking. International Journal of Computer Vision, 35(1):45--63, 1999.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....contrary, many approaches try to select the optimal cue for the actually perceived context. Usage of a single, predominant cue supported by other, often less reliable, cues is another scheme often described. The layered hierarchy of vision based tracking algorithms proposed by Toyama and Hager [13,14] is a good example of the cue selection approach. Their declared goal is to enable robust, adaptive tracking in real time. Different tracking algorithms are selected with respect to the actual conditions: Whenever conditions are good, an accurate and precise tracking algorithm is employed. When ....

Toyama K, Hager G (1999) Incremental focus of attention for robust vision-based tracking. Int J Comput Vision 35(1): 45--63

....wavelet networks in such a way as to avoid significant geometric deviations while offering enough flexibility that local distortions can still be modeled. 3 Implementation WaveBase was developed to provide initialization for GazeMaster s 3D facial pose tracker. The tracking system (described in [2, 3]) uses nine tracked features on a subject s face inner and outer corners of both eyes, three points on the nose, and two mouth corners. Each feature is tracked by a combination of lowresolution, sum of absolute differences template matching and iterative sub pixel tracking of small image ....

KentaroToyama and G. Hager, Incremental Focus of Attention for Robust Vision-Based Tracking, International Journal of Computer Vision, 35(1):45-63, 1999.

....channels. On the contrary, many approaches try to select the optimal cue for the actually perceived context. Also common is to use a single, predominant cue supported by other, often less reliable cues. The layered hierarchy of vision based tracking algorithms proposed by Toyama and Hager [13,12] is a good example for the cue selection approach. Their declared goal is to enable robust, adaptive tracking in real time. Di#erent tracking algorithms are selected with respect to the actual conditions: Whenever conditions are good, an accurate and precise tracking algorithm is employed. When ....

K. Toyama and G.Hager. Incremental focus of attention for robust vision-based tracking. International Journal of Computer Vision, 1999.

....channels. On the contrary, many approaches try to select the optimal cue for the actually perceived context. Also common is to use a single, predominant cue supported by other, often less reliable cues. The layered hierarchy of vision based tracking algorithms proposed by Toyama and Hager [13, 12] is a good example for the cue selection approach. Their declared goal is to enable robust, adaptive tracking in real time. Different tracking algorithms are selected with respect to the actual conditions: Whenever conditions are good, an accurate and precise tracking algorithm is employed. When ....

K. Toyama and G.Hager. Incremental focus of attention for robust vision-based tracking. International Journal of Computer Vision, 1999.

....of attention systems work by looking for features usually defined by some explicit or implicit model. The search may take many forms, from multiresolution approaches that emulate human vision s peripheral and foveal vision, to target recognition methods that use explicit templates for matching [4, 5, 6, 7]. Once a set of attention regions has been detected, a second stage of processing is often used to further process them, or to rank them. This processing may require more complex algorithms, but they are applied only to small regions of the image. In this paper, we describe an approach to feature ....

K. Toyama and G. Hager, "Incremental focus of attention for robust vision-based tracking," Int. J. Computer Vision, vol. 35, no. 1, pp. 45--63, 1999.

....by several authors. Crowley Parker 1984, Crowley Sanderson 1987) detected peaks and ridges in a pyramid representation. In retrospect, a main reason why stability problems were encountered is that the pyramids involved a rather coarse sampling in 2 According to the terminology proposed by (Toyama Hager 1999), the automatic scale selection mechanism is essential for the pre failure robustness of the feature tracker, while the proposed qualitative multi scale feature hierarchy improves the post failure robustness. the scale direction. Koenderink 1984) defined links across scales using iso intensity ....

Toyama, K. & Hager, G. (1999), `Incremental focus of attention for robust vision-based tracking', Int. J. of Computer Vision . to appear.

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....many systems lack the robustness required for practical application tracking is unable to handle or recover from situations such as occlusion or exit from the field of view. This paper presents a cursor control system that uses face tracking based on Incremental Focus of Attention (IFA) [20]. The next section describes the face tracking subsystem, which is able to track the 3D pose of a single user s face at 30Hz. It rapidly recovers from moments of tracking failure caused by visual disturbances and does so without being distracted by other faces in the field of view. Section 3 ....

....that disrupts normal tracking [19] 2. 1 Incremental Focus of Attention Reliable face tracking is accomplished by implementing a system based on Incremental Focus of Attention (IFA) an architecture for incorporating different tracking algorithms into a robust real time tracking system [18, 20]. If designed for the face tracking task, IFA allows tracking of 3D pose when conditions are favorable (i.e. all facial features are visible) and additionally performs rapid recovery from moments of tracking failure. A brief description of the IFA face tracking system follows (a more rigorous ....

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K. Toyama and G. Hager. Incremental focus of attention for robust vision-based tracking. Int'l J. of Computer Vision, 1999.

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K. Toyama and G. Hager. Incremental focus of attention for robust vision-based tracking. International Journal of Computer Vision, 35(1):45--63, 1999.

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K. Toyama and G. Hager, "Incremental focus of attention for robust vision-based tracking," International Journal of Computer Vision 35(1), pp. 45--63, 1999.

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Toyama K,Hag/ G. Incremental focus of attention for robust vision-basedtracking International Journal of Computer Vision 1999;35(1):45--63.

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Toyama, K., Hager, G.: Incremental focus of attention for robust vision-based tracking. IJCV 35 (1999) 45--63

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K. Toyama. Incremental focus of attention for robust vision-based tracking. International Journal of Computer Vision, 35(1):45--63, 1999.

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K. Toyama and G.D. Hager. Incremental focus of attention for robust vision-based tracking. Int. Journal of Computer Vision, 35(1):45--63, 1999.

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K. Toyama and G. Hager. Incremental focus of attention for robust vision-based tracking. International Journal of Computer Vision, 35(1):45--63, 1999.

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Toyama, K. and Hager, G., "Incremental focus of attention for robust vision-based tracking," International Journal of Computer Vision, vol. 35, no. 1, pp. 45-63, 1999.

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