Color based video segmentation using level sets

Harper, P.; Reilly, Richard B.

doi:10.1109/icip.2000.899450

Cited by 10 publications

(2 citation statements)

References 15 publications

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“…We can observe that our method outperforms the state-of-art ones. Indeed, techniques like (Harper and Reilly, 2000) applying skin-color tests usually oversegment images, such as Fig. 2 (a), containing many visible body parts which are not only faces.…”

Section: Experiments and Discussionmentioning

confidence: 99%

“…Hence, some automatic initialization techniques more specific for face detection have been developed, and mainly rely on skin color information (Hanmin and Zhen, 2008), (Harper and Reilly, 2000), but they are not robust if other body parts are visible as well. Approaches using the elliptical shape detection (Huang and Su, 2004) fail in presence of other ellip- tical foregrounds in an image, while those computing the interframe difference (Zhou et al, 2010), (Bajpai et al, 2011) are restricted to image sequences.…”

Section: Introductionmentioning

confidence: 99%

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Multi-scale, Multi-feature Vector Flow Active Contours for Automatic Multiple Face Detection

Olszewska¹

2013

Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing

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Abstract:To automatically detect faces in real-world images presenting challenges such as complex background and multiple foregrounds, we propose a new method which is based on parametric active contours and which does not require any supervision, model nor training. The proposed face detection technique computes multi-scale representations of an input color image and based on them initializes the multi-feature vector flow active contours which, after their evolution, automatically delineate the faces. In this way, our computationally efficient system successfully detects faces in complex pictures with varying numbers of persons of diverse gender and origins and with different types of face views (front/profile) and variate face alignments (straight/oblique), as demonstrated in tests carried out on several datasets.

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Section: Experiments and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%