Active Vision from Multiple Cues.
ABSTRACT Active vision involves processes for stabilisation and fixation on objects of interest. To provide robust performance for
such processes it is necessary to consider integration and processing as closely coupled processes. In this paper we discuss
methods for integration of cues and present a unified architecture for active vision. The performance of the approach is illustrated
by a few examples.
- SourceAvailable from: summerschool2011.esmcs.eu[show abstract] [hide abstract]
ABSTRACT: Fixation is the link between the physical environment and the visual observer, both of which can be dynamic. That is, dynamic fixation serves the task of preserving a reference point in the world, despite relative motion. In this respect, fixation is dynamical in two senses: in response to voluntary changes of fixation point or attentive cues-gaze shiftings, and in response to the desire to compensate for the retinal slip-gaze holding.International Journal of Computer Vision 01/1996; 17:113-135. · 3.62 Impact Factor
Article: Integrating primary ocular processes[show abstract] [hide abstract]
ABSTRACT: The study of active vision using binocular head-eye systems requires answers to some fundamental questions in control of attention. This paper presents a cooperative solution to resolve the ambiguities generated by the processes engaged in fixation. We suggest an approach based on integration of these processes, resulting in cooperatively extracted unique solutions. The discussion begins by looking at biological vision. Based on this discussion, a model of integration for machine vision is suggested. The implementation of the model on the KTH-head — a head-eye system simulating the essential degrees of freedom in mammalians — is explained, and in this context the primary processes in the head-eye system are briefly described. The major stress is put on the idea that the rivalry processes in vision in general, and the head's behavioural processes in particular, results in a reliable outcome. As an experiment, the ambiguities raised by fixation at repetitive patterns is tested; the cooperative approach proves to handle the problem correctly and find a unique solution for the fixation point dynamically and in real-time.Image and Vision Computing. 01/1992;
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ABSTRACT: In this paper we discuss how figure-ground segmentation can be important in deriving object properties such as shape. Our approach is based on a conjunction of motion and depth. The main idea is to produce a 2-dimensional histogram with depth in one dimension and horizontal motion in the other. This histogram is then analyzed. The most significant peaks in the histogram are backprojected to the image to produce an object mask. This object mask is maintained over time.03/1998;