Abwooi-Computer vision is one out of many areas thaf wants to understand the process of human functianaliIy and copy that pmecrr with intention to eomplemcnt human life with intelligent machines. For better human-eomputer interaction i t i s n~c e s~a r y for the machine to see people. This can be achieved by empiqing face detection algorithms, like thc one used in the in~taiisrien"15 Seconds O f F i m C " . Mentioned installation unites the areas o f modern an and technology. Its algorithm i s based an skin colour detection. Onc of the pmhiemr thii and Similar slgnrithmE have to deal with i s renritiviry to the illumination conditions under which the input image i s captured. Hence illumination sensitivity influences face detection rer~lts. O m o f the aspects lrom which we can observe illumination influence i s the choke of the pmper colour $pace. Since some coloui spaces are designed to eliminate the influence o f illumination (brightness) whendescribing colour o f an object, an idea of using such P colour space for skiinsolour detection has been taken under consideration and some of the methods have been researched and tested.Kepmf-computer vision, automatic detection, human face, lace candidates search, rkin-eolour determination, 2D colour space. 3D colour space, illumination independence. INTROOUCTiON A. Installution "15 Seconds of Fame"The installation "15 Seconds of Fame" [7] is an interactive art installation, which intends to make instant celebrities out of common people by putting their portraits on the museum wall. The idea was inspired by the quotation ofthe famous artist Andy Warhol: "In the future everybody will he famous for fifteen minutes" and by the pop-an style of his work. The installation looks like a valuable framed picture (Fig. 1). LCD monitor and digital camera are built into the picture. Camera is connected to a computer, which controls the camera and processes captured images. Special software contains algorithm for face detection, which Fig. I . LCO computcr monitardrcsscd up like a prccious painting. Thc round apcning above the picNre is for thc digital camcra Icns. with the following rules [6], [7], which describe the skin cluster in the RGB colour space: % The skin colour at uniform daylight illumination R > 95 AND G > 40 AND B > 20 A N 0 m a x ( R , G . B ) -min(R,G.B) > 15AND % RGB camponcnts must not bc dose togcthcr -% grcyness elimination Yo also R and G components m u 1 nor bc dose togcthcr -% othewisc wc arc not dealing with the fair compicxian IR -GI > 15 AN0 R > G AND R > B OR % R component must bc the greaiest coinponcnl looks for faces in captured images. Among them it chooses one for further processing. In the next step a randomly chosen %The skin ~,.I ","-, ,,,,-ill,:"l ~ or (light) daylight The face detection algorithm that is used by the installation "15 Seconds of Fame" [7] uses 3D colour space (RGB) for detecting skin colour pixels. With the help of heuristic rules it is determined, whether a certain pixel o f input image corresponds to the skin colour. Note that t...
Computer vision is one out of many areas that want to understand the process of human functionality and copy that process with intention to complement human life with intelligent machines. For better human-computer interaction it is necessary for the machine to see people. This can be achieved by employing face detection algorithms, like the one used in the installation "15 Seconds of Fame" [7]. Mentioned installation unites the areas of modern art and technology. Its algorithm is based on skin colour detection. One of the problems this and similar algorithms have to deal with is sensitivity to the illumination conditions under which the input image is captured. Hence illumination sensitivity influences face detection results. One of the aspects from which we can observe illumination influence is the choosing of the proper colour space. Since some colour spaces are designed to eliminate the influence of illumination when describing colour of an object, an idea of using such a colour space for skin-colour detection was taken under consideration and some of the methods were researched and tested.
Humans are able to recognize small number of people they know well by the way they walk. This ability represents basic motivation for using human gait as the means for biometric identification. Such biometrics can be captured at public places from a distance without subject's collaboration, awareness, and even consent. Although current approaches give encouraging results, we are still far from effective use in real-life applications. In general, methods set various constraints to circumvent the influence of covariate factors like changes of walking speed, view, clothing, footwear, and object carrying, that have negative impact on recognition performance. In this paper we propose a skeleton model based gait recognition system focusing on modelling gait dynamics and eliminating the influence of subjects appearance on recognition. Furthermore, we tackle the problem of walking speed variation and propose space transformation and feature fusion that mitigates its influence on recognition performance. With the evaluation on OU-ISIR gait dataset, we demonstrate state of the art performance of proposed methods.
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