Alternative Search Techniques for Face Detection Using Location Estimation and Binary Features
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Humans have the ability to learn. Having seen an object we can recognise it later. We can do this because our nervous system uses an efficient and robust visual processing and capabilities to learn from sensory input. On the other hand, designing algorithm ...
We present a new approach for the design of optimal steerable 2-D templates for feature detection. As opposed to classical schemes where the optimal 1-D template is derived and extended to 2-D, we directly obtain the 2-D template. We choose the template fr ...
Boosting-based methods have recently led to the state-of-the-art face detection systems. In these systems, weak classifiers to be boosted are based on simple, local, Haar-like features. However, it can be empirically observed that in later stages of the bo ...
In this paper we study the behavior of local descriptor object recognition methods with respect to 3D geometric transformations and image resolution variations. As expected performance decreases with accentuated perspective and decrease in resolution. To i ...
In this paper we propose a new, interactive technique for the segmentation of elongated structures in images. It is based on the so-called live-wire segmentation paradigm and uses a newly developed steerable filter for computing local ridge strength and or ...
In this thesis, we present a coherent and consistent approach for the estimation of shape and shape attributes from noisy images. As compared to the traditional sequential approach, our scheme is centered on a shape model which drives the feature extractio ...
Change detection generally is the difference between images. The differences or changes could be due to moving objects or a variation of illumination. In general the goal is to extract only changes due to moving object that occur int eh scene, and to ignor ...
When comparing different methods for face detection or localization, one realizes that just simply comparing the reported results is misleading as, even if the results are reported on the same dataset, different authors have different views of what a corre ...