caa a22 4500 469036311 CHVBK 20180323132757.0 cr unu---uuuuu 170328e19920101xx s 000 0 eng 10.1007/BF00128132 doi (NATIONALLICENCE)springer-10.1007/BF00128132 Tsotsos John Department of Computer Science, University of Toronto, M5S 1A1, Toronto, Ontario aut On the relative complexity of active vs. passive visual search [Elektronische Daten] [John Tsotsos] Here, this author attempts to tie the concept of active perception to attentive processing in general and to the complexity level analysis of visual search described previously; the aspects of active vision as they have been currently described form a subset of the full spectrum of attentional capabilities. Our approach is motivated by the search requirements of vision tasks and thus we cast the problem as one of search preceding the application of methods for shape-from-X, optical flow, etc., and recognition in general. This perspective permits a dimension of analysis not found in current formulations of the active perception problem, that of computational complexity. This article describes where the active perception paradigm does and does not provide computational benefits along this dimension. A formalization of the search component of active perception is presented in order to accomplish this. The link to attentional mechanisms is through the control of data acquisition and processing by the active process. It should be noted that the analysis performed here applies to the general hypothesize-and-test search strategy, to time-varying scenes as well as to the general problem of integration of successive fixations. Finally, an argument is presented as to why this framework is an extension of the behaviorist approaches to active vision. Kluwer Academic Publishers, 1992 International Journal of Computer Vision Kluwer Academic Publishers 7/2(1992-01-01), 127-141 0920-5691 7:2<127 1992 7 11263 https://doi.org/10.1007/BF00128132 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00128132 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Tsotsos John Department of Computer Science, University of Toronto, M5S 1A1, Toronto, Ontario aut NATIONALLICENCE 773 0- International Journal of Computer Vision Kluwer Academic Publishers 7/2(1992-01-01), 127-141 0920-5691 7:2<127 1992 7 11263 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer