MULTRAK: a system for automatic multiperson localization and tracking in real-time

Bernier, Olivier; Collobert, M.; Féraud, Raphaël; Lemaire, Vincent; Viallet, J.E.; Collobert, D.

doi:10.1109/icip.1998.723444

Cited by 14 publications

(5 citation statements)

References 6 publications

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“…On a small test set of 42 images, they report a detection rate similar to [126]. The method has also been employed in LISTEN [23] and MULTRAK [8].…”

Section: Neural Networkmentioning

confidence: 90%

Detecting faces in images: a survey

Yang

Kriegman

Ahuja

2002

IEEE Trans. Pattern Anal. Machine Intell.

2,605

117

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ÐImages containing faces are essential to intelligent vision-based human computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation, and expression recognition. However, many reported methods assume that the faces in an image or an image sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Given a single image, the goal of face detection is to identify all image regions which contain a face regardless of its three-dimensional position, orientation, and the lighting conditions. Such a problem is challenging because faces are nonrigid and have a high degree of variability in size, shape, color, and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics, and benchmarking. After analyzing these algorithms and identifying their limitations, we conclude with several promising directions for future research.

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“…On a small test set of 42 images, they report a detection rate similar to [126]. The method has also been employed in LISTEN [23] and MULTRAK [8].…”

Section: Neural Networkmentioning

confidence: 90%

Detecting faces in images: a survey

Yang

Kriegman

Ahuja

2002

IEEE Trans. Pattern Anal. Machine Intell.

2,605

117

View full text Add to dashboard Cite

show abstract

“…The prenetwork is a single multilayer perceptron (MLP) [4], [30], [36]. It has 300 inputs, corresponding to the size of the extracted subwindows, 20 hidden neurons, and one output (face/nonface), for a total of 6,041 weights.…”

Section: Hypothesis Eliminationmentioning

confidence: 99%

A fast and accurate face detector based on neural networks

Feraund

Bernier

Viallet

et al. 2001

IEEE Trans. Pattern Anal. Machine Intell.

Self Cite

235

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ÐDetecting faces in images with complex backgrounds is a difficult task. Our approach, which obtains state of the art results, is based on a new neural network model: the Constrained Generative Model (CGM). Generative, since the goal of the learning process is to evaluate the probability that the model has generated the input data, and constrained since some counterexamples are used to increase the quality of the estimation performed by the model. To detect side view faces and to decrease the number of false alarms, a conditional mixture of networks is used. To decrease the computational time cost, a fast search algorithm is proposed. The level of performance reached, in terms of detection accuracy and processing time, allows to apply this detector to a real world application: the indexation of images and videos.

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“…Bernier et al describes an automatic camera zooming system using a face recognition technique [1]. This relieves users from minor camera adjustments.…”

Section: Shingo Uchihashimentioning

confidence: 99%

Direct camera control for capturing meetings into multimedia documents

Uchihashi¹

2001

IEEE International Conference on Multimedia and Expo, 2001. ICME 2001.

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Currently, only experts can manage to capture activities in a conference room using multiple cameras because of the complexity of the task. We conducted interviews with experienced operators as well as video analysis on their outputs. Typical design of user interface for camera control was found out to be demanding users a lot of internal computations. A new interface for direct camera control is introduced to overcome the problem and tested in a real environment. The results well supported our usage model and proved our interface is effective.

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MULTRAK: a system for automatic multiperson localization and tracking in real-time

Cited by 14 publications

References 6 publications

Detecting faces in images: a survey

Detecting faces in images: a survey

A fast and accurate face detector based on neural networks

Direct camera control for capturing meetings into multimedia documents

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