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- Ardö, Håkan, et al.
(författare)
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Flow Counting Using Realboosted Multi-sized Window Detectors
- 2012
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Ingår i: Computer Vision – ECCV 2012. Workshops and Demonstrations : Florence, Italy, October 7-13, 2012, Proceedings, Part III - Florence, Italy, October 7-13, 2012, Proceedings, Part III. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 1611-3349 .- 0302-9743. - 9783642338847 - 9783642338854 ; 7585, s. 193-202
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Konferensbidrag (refereegranskat)abstract
- One classic approach to real-time object detection is to use adaboost to a train a set of look up tables of discrete features. By utilizing a discrete feature set, from features such as local binary patterns, efficient classifiers can be designed. However, these classifiers include interpolation operations while scaling the images over various scales. In this work, we propose the use of real valued weak classifiers which are designed on different scales in order to avoid costly interpolations. The use of real valued weak classifiers in combination with the proposed method avoiding interpolation leads to substantially faster detectors compared to baseline detectors. Furthermore, we investigate the speed and detection performance of such classifiers and their impact on tracking performance. Results indicate that the realboost framework combined with the proposed scaling framework achieves an 80% speed up over adaboost with bilinear interpolation.
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| 3. |
- Ardö, Håkan, et al.
(författare)
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Foreground Estimation and Hidden Markov Models for Tracking
- 2005
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We will give a short introduction to foreground/background estimation and Hidden Markov fortracking. More information about the topics can be found in the papers listed at the end.
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| 5. |
- Ardö, Håkan, et al.
(författare)
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Real time viterbi optimization of hidden Markov Models for multi target tracking
- 2007
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Ingår i: 2007 IEEE Workshop on Motion and Video Computing (WMVC'07). - 0769527930
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Konferensbidrag (refereegranskat)abstract
- In this paper the problem of tracking multiple objects in image sequences is studied. A Hidden Markov Model describing the movements of multiple objects is presented. Previously similar models have been used, but in real time system the standard dynamic programming Viterbi algorithm is typically not used to find the global optimum state sequence, as it requires that all past and future observations are available. In this paper we present an extension to the Viterbi algorithm that allows it to operate on infinite time sequences and produce the optimum with only a finite delay. This makes it possible to use the Viterbi algorithm in real time applications. Also, to handle the large state spaces of these models another extension is proposed. The global optimum is found by iteratively running an approximative algorithm with higher and higher precision. The algorithm can determine when the global optimum is found by maintaining an upper bound on all state sequences not evaluated. For real time performance some approximations are needed and two such approximations are suggested. The theory has been tested on three real data experiments, all with promising results.
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| 6. |
- Berthilsson, Rikard
(författare)
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A Statistical Theory of Shape
- 1998
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Ingår i: Advances in Pattern Recognition. Joint IAPR International Workshops SSPR'98 and SPR'98. Proceedings. - 3 540 64858 5 ; , s. 677-686
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We study the statistical theory of shape for ordered finite point configurations, or otherwise stated, the uncertainty of geometric invariants. A general approach for defining shape and finding its density, expressed in the densities for the individual points, is developed. Some examples that can be computed analytically are given, including both affine and positive similarity shape. Projective shape and projective invariants are important topics in computer vision and are also discussed
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| 8. |
- Berthilsson, Rikard
(författare)
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Affine Correlations
- 1998
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Ingår i: [Host publication title missing]. ; 2, s. 1458-1460
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We propose a method for maximising the affine correlation between images. The method is more global in its search than for example steepest descent based methods. In a first approximation, there is no need to compute any derivatives and it is shown that the results are very good. The method is based on certain changes of coordinates in the images and extensive use of the fast Fourier transformation (FFT). This makes the method very fast, when implemented on a computer
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