| 1. |
- Kristanl, Matej, et al.
(författare)
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The Seventh Visual Object Tracking VOT2019 Challenge Results
- 2019
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Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
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| 2. |
- Kristan, Matej, et al.
(författare)
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The Sixth Visual Object Tracking VOT2018 Challenge Results
- 2019
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Ingår i: Computer Vision – ECCV 2018 Workshops. - Cham : Springer Publishing Company. - 9783030110086 - 9783030110093 ; , s. 3-53
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).
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| 3. |
- Kristan, Matej, et al.
(författare)
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The Visual Object Tracking VOT2015 challenge results
- 2015
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Ingår i: Proceedings 2015 IEEE International Conference on Computer Vision Workshops ICCVW 2015. - : IEEE. - 9780769557205 ; , s. 564-586
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. The dataset, the evaluation kit as well as the results are publicly available at the challenge website(1).
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| 4. |
- Kristan, Matej, et al.
(författare)
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The Visual Object Tracking VOT2016 Challenge Results
- 2016
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Ingår i: COMPUTER VISION - ECCV 2016 WORKSHOPS, PT II. - Cham : SPRINGER INT PUBLISHING AG. - 9783319488813 - 9783319488806 ; , s. 777-823
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment.
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| 5. |
- Felsberg, Michael, 1974-, et al.
(författare)
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The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results
- 2016
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Ingår i: Computer Vision – ECCV 2016 Workshops. ECCV 2016.. - Cham : SPRINGER INT PUBLISHING AG. - 9783319488813 - 9783319488806 ; , s. 824-849
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Konferensbidrag (refereegranskat)abstract
- The Thermal Infrared Visual Object Tracking challenge 2016, VOT-TIR2016, aims at comparing short-term single-object visual trackers that work on thermal infrared (TIR) sequences and do not apply pre-learned models of object appearance. VOT-TIR2016 is the second benchmark on short-term tracking in TIR sequences. Results of 24 trackers are presented. For each participating tracker, a short description is provided in the appendix. The VOT-TIR2016 challenge is similar to the 2015 challenge, the main difference is the introduction of new, more difficult sequences into the dataset. Furthermore, VOT-TIR2016 evaluation adopted the improvements regarding overlap calculation in VOT2016. Compared to VOT-TIR2015, a significant general improvement of results has been observed, which partly compensate for the more difficult sequences. The dataset, the evaluation kit, as well as the results are publicly available at the challenge website.
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| 6. |
- Chen, XÍ, et al.
(författare)
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TDHQ Enabling Fine-granularity Adaptive Loading for SSB-DMT Systems
- 2018
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Ingår i: IEEE Photonics Technology Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1041-1135 .- 1941-0174. ; 30:19, s. 1687-1690
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Tidskriftsartikel (refereegranskat)abstract
- In this letter, we introduce time domain hybrid quadrature amplitude modulation (TDHQ) for the single sideband (SSB) discrete multi-tone (DMT) systems. Experimental results reveal that with a single precoding set and the proposed adaptive loading algorithm, the TDHQ scheme can achieve finer granularity and therefore smoother continuous growth of data rate than that with the conventional quadrature amplitude modulation (QAM). Besides, thanks to the frame construction and the tailored mapping rule, the scheme with TDHQ has an obviously better peak to average power ratio (PAPR).
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| 7. |
- Jiang, Tao, et al.
(författare)
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Investigation of DC-Biased Optical OFDM With Precoding Matrix for Visible Light Communications : Theory, Simulations, and Experiments
- 2018
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Ingår i: IEEE Photonics Journal. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1943-0655. ; 10:5
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Tidskriftsartikel (refereegranskat)abstract
- Orthogonal frequency-division-multiplexing (OFDM) technology is widely used in visible light communication (VLC) to achieve high data rate transmission. However, the traditional direct-current (DC)-biased optical OFDM (DCO-OFDM) VLC systems suffer from the high peak-to-average power ratio (PAPR) which causes signal clipping distortion, and, thus, performance degradation. Furthermore, severe high-frequency fading due to the limited system bandwidth results in poor bit error rate (BER) performance. Precoding matrix (PM) techniques have been proposed to enhance the performance of VLC OFDM transmission, but a little or no work has been carried out in investigating the theory of PM used in OFDM VLC systems. In this paper, we aim to reveal the theory of PM-DCO-OFDM for a VLC system. To figure out the intrinsic laws of a PM method, we investigate the principles of PAPR reduction, clipping distortion optimization, and signal-to-noise ratio (SNR) distribution equalization. Based on the analysis of PAPR, we theoretically proved the simplicity of PM as a method to reduce the possibility of high PAPR by improving the autocorrelation performance of input symbols. The clipping distortion could be improved due to the reduction of high PAPR. Moreover, the relatively uniform SNR distribution can be achieved by PM through equalizing the clipping and channel noise, which is beneficial to improve the BER performance in high-frequency constrained systems. However, the PM method used in a DCO-OFDM VLC system should consider the transmitting power, modulation format, and transmission distance as a whole to achieve the transmission performance improvement. The simulation results demonstrate the complementary cumulative distribution function of PAPR can be reduced similar to 3 dB, while the performance of clipping distortion power and clipping error probability are significantly improved. Furthermore, experiment is carried out with results showing that the PM method can improve the BER performance in the case that VLC OFDM transmission has enough transmitting power, but with the low transmitting power, the PM also can damage the BER performance. The simulation and experiment results are consistent with our theoretical analysis.
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