Lim, I. S

Thalmann, D

Infoscience - École polytechnique fédérale de Lausanne

Proceedings of ACM Symposium on Applied Computing (SAC 2000), pp. 570 - 573, March 2000, Como, Italy.Tournament Selection for Browsing Temporal Signals  Ik Soo Lim and Daniel ThalmannComputer Graphics Lab (LIG)Swiss Federal Institute of Technology (EPFL)CH-1015 Lausanne, Switzerlandiksoolim@email.com, thalmann@lig.di.epfl.chAbstractPresentation of audio or video files for browsing is difficultdue to their serial and transitory nature whereas texts or pho-tos may be simply placed in the user’s visual field. This pa-per describes a simple technique for browsing and selectingamong temporal signals such as audio and video. In the pro-posed method, only two among a set of the signals are pre-sented to the user at a time and (s)he just needs to select a‘winner’ among the two. This process is repeated for manyrounds until a single winner remains as analogous to the tour-nament match in many sport games. We applied this intu-itive technique to browsing and selecting among computer-animation clips for motion parameter setting. It would alsobe applicable to browsing/selecting among retrieved candi-dates in audio/video retrieval systems.Key Words: browsing, retrieval, tournament, multimedia,audio, video, user interface.1 IntroductionBrowsing in a visual user interface takes advantage of the fact that avariety of artifacts may be placed in the visual field and the user canrapidly scan them, as well as use peripheral vision to obtain somesense of the objects not in the immediate visual focus [8]. Presen-tation of a set of retrieved items is usually done this way in imageretrieval systems [5][6]: the user can rapidly scan them and choosethe best among them. However, presentation of temporal signalssuch as audio or video files for browsing is made difficult by theserial and transitory nature of them. As opposed to the static dis- This work is supported in part by PAVR under the EU Trainingand Mobility of Researchers program.play, audio/video files must be played over time. Presenting manyaudio/video files at a time to the user, hence, have some difficulties.Resources are often not available enough for the simultaneous play-backs. Listening/watching many audio/video clips simultaneouslyis hardly an easy task for human users.There are some attempts to get around these problems such asspatialized audio presentation [8] and graphical display of a key-frame extracted from each of video files [3] or computer animationclips [5]. Even these get-arounds have, however, their own prob-lems. The spatialized audio burdens the human user on frequentrecalling from spatial memory in the absence of visual cues. It isnot always possible to extract a key-frame that represents the entirevideo/animation clip well enough. We present a simple and intu-itive way of browsing the temporal signals without much load onthe user’s memory nor the non-representative simplification suchas the key-frame extracting. In Section 2, the idea of tournamentbrowsing is explained and Section 3 presents its application to in-teractive evolution system of computer animation clip. Discussionand Conclusions follow it.2 Tournament Browsing and Selec-tionInitially, the entire set of the candidates is in the tournament: ina retrieval system, this set would correspond to that of retrieveditems which are highly ranked for a given query. Two candidatesare selected and presented for playback to the human user. The userjust needs to choose a ‘winner’ among the two. Only the winnerprogresses to the next level of the tournament. The tournamentcontinues until a single winner remains. The ranking of a candidateis its height in the playoff tree (Figure 1). The one at the top is thenthe favourite choice of the user. The total number of ‘competitions’for a set of  candidates is  .We experimented this tournament browsing technique in our in-teractive evolution system of generating variations on a prototypemotion in 3D computer animation.3 Interactive Evolution of MotionMotion control of articulated figures such as humans has been aFigure 1: Tournament selection and ranking. Each horizontal line designating a competition and each upward arrow designating thewinner progressing in the tournament. The ranking of a candidate is its height in the playoff tree. (Adopted from [1].)challenging task in computer animation [2]. Once an acceptablemotion segment has been created, either from key-framing, motioncapture or physical simulations, reuse of it is important. Much ofthe recent research in it has been directed towards mixing those se-lected from a library of example motions to create a new motion[7][13]: for example, a library of walk motions. Though it greatlyexpands the range of possible motions, it is difficult to acquire theexamples in the beginning: it still has to go through tedious key-framing, motion capture or physical simulations. Using interactiveevolution, a genetic algorithm technique, however, we can synthe-sise more example motions from a single prototype motion such asdifferent walk styles out of a normal walk motion without tedioususer specifications, design efforts, or knowledge of algorithmic de-tails. This can be useful since it is much easier than animating fromscratch.Application of interactive evolution in computer graphics ishardly new. For example, it is used very effectively in creatingbeautiful and abstract colour images [9]. An initial population ofimages generated randomly by the computer is displayed on thescreen. From the displayed set the user determines a relative fit-ness ranking. The mating and/or mutation operations are applied tothe selected images based on the ranking to produce a new set ofprogeny images, that supply the input for the next round of user se-lection. This process is repeated multiple times, to evolve an imageof interest to the user.When applying this interactive evolution technique to animation,displaying population of animation clips to the user faces the prob-lems discussed in Section 1.3.1 ExperimentIn our interactive evolution system of motion[4], the initial popula-tion consists of random variations on a given prototype animationclip. Only two among, say, eight animation clips in the popula-tion are shown at a time whereas all of them would be displayed onthe screen simultaneously when evolving images or shapes [9][12].The human user just needs to click what (s)he favours over the otherand repeat this process for each pair of animation clips presented(Figure 2.) Once the final winner is determined this way, the rank-ing for each candidate is used as its relative fitness. Then, the restof other processes are similar to those of other interactive evolutionapplications [9][12]. The mating and/or mutation operations are ap-plied to the selected motions based on the ranking to produce a newset of progeny motions, that supply the input for the next round ofuser selection. This process is repeated multiple times, to evolve amotion of interest to the user.We use a humanoid model of 62 degrees of freedom both ani-mated and rendered using an in-house software based on OpenGL:description of other details about the system is beyond the scopeof this paper. Figure 3 shows the snapshots of the original proto-type motion and its variations generated by the interactive evolutionsystem: it took only a few minutes or dozens of mouse clicks forreaching the shown variations.4 Discussion and ConclusionThis tournament scheme contains a sort of noise associated with itsability to rank any given set [1]. How accurately the tournamentranks the set depends on the competitors met. If the best candidatein the set competes in the initial round of the tournament with thesecond best one, only the best one moves up the hierarchy whereasthe other being assigned the lowest rank. All the candidates thatlose at the same level of the tournament have the same rank, whichde-emphasises their ranks relative to each other. This is, however,more beneficial than over-committing to an exhaustingly completeordering of the set. Resulting tournament hierarchy is sufficientinformation for our interactive evolution application as describedabove: selecting the best one, based on user’s subjective judgement,among the set of retrieved ones rather than complete reordering ofthem is often enough in many applications of retrieval systems.The notion of tournament competition has been also applied tostandard genetic algorithms where all the processes including selec-tion of a winner are done in a batch mode without any interactiveintervention of the human user [1][10]. While it is all about evolv-ing better solutions for complex tasks in a batch mode, our novelapplication reported here is about user interface and usability ininteractive systems.In summary, we have applied tournament selection to browsinga set of animation clips. It gets around the difficulties which pre-sentation of temporal signals such as audio or video files typicallyfaces. It is simple, intuitive and also applicable to retrieval systems(a) (b)Figure 2: (a) Only Two at a Time. Two among eight animation clips of motions are presented to the user at a time and the user just needsto choose one among them. (b) Progress Gauge of Tournament. This gauge displays the current status of the tournament.of sound/video.5 AcknowledgementsWe thank Joaquim Esmerado, Anthony Guye-Vuilleme and OlivierRenault for their helpful discussions.References[1] P. J. Angeline, J. B. Pollack. Competitive Environments Evolve Bet-ter Solutions for Complex Tasks. Proceedings of the Third Interna-tional Conference on Genetic Algorithms, pp. 264-270. 1993.[2] N. Badler, C. Phillips and B. Webber. Simulating Humans: ComputerGraphics, Animation, and Control. Oxford University Press, 1993.[3] S. Chang, et al. VideoQ: An Automated Content Based Video SearchSystem Using Visual Cues. Proceedings of ACM Multimedia ’97, pp.313-324. November 9-13, 1997. Seattle, Washington, USA.[4] I. S. Lim and D. Thalmann. Pro-actively Interactive Evolution forComputer Animation. Proceedings of Eurographics Workshop onAnimation and Simulation ’99 (CAS ’99), pp. 45 - 52, September1999, Milan, Italy.[5] J. Marks, et al. Design Galleries: a General Approach to SettingParameters for Computer Graphics and Animation. Proceedings ofACM SIGGRAPH ’97, pp.389-400, 1997.[6] M. Ortega, et al. Supporting Similarity Queries in MARS. Proceed-ings of ACM Multimedia ’97, pp. 403-413. November 9-13, 1997.Seattle, Washington, USA.[7] C. Rose, M. F. Cohen and B. Bodenheimer. Verbs and Adverbs: Mul-tidimensional Motion Interpolation. IEEE Computer Graphics andApplications, pp. 32-40, September/October 1998.[8] C. Schmandt. Audio Hallway: a Virtual Acoustic Environment forBrowsing. Proceedings of ACM UIST ’98, pp. 163-170. November1-4, 1998. San Francisco, Califonia, USA.[9] K. Sims. Interactive Evolution of Equations for Procedural Models.The Visual Computer, v9, pp. 466-476, 1993.[10] K. Sims. Evolving 3D Morphology and Behavior by Competition.Artificial Life, v1, pp. 353-372, 1994.[11] Y. Taniguchi, A. Akutsu, Y. Tonomura. PanoramaExcerpts: Extract-ing and Packing Panoramas for Video Browsing. Proceedings ofACM Multimedia ’97, pp. 427-436. November 9-13, 1997. Seattle,Washington, USA.[12] S. Todd, W. Latham and P. Hughes. Computer Sculpture Design andAnimation. Journal of Visualization and Computer Animation, v2,pp. 98-105, 1991.[13] D. Wiley and J. K. Hahn. Interpolation Synthesis of Articulated Fig-ure Motion. IEEE Computer Graphics and Applications, pp. 39-45,November/December 1997.(a)(b)(c)(d)(f)Figure 3: Variations on a Theme. (a) The key frames of the original prototype motion, come-in, composed by hands. (b-f) The variationsgenerated out of the prototype using the interactive evolution system.

Tournament Selection for Browsing Temporal Signal

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Tournament Selection for Browsing Temporal Signal

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