A new obstacle detection algorithm for unmanned surface vehicles (USVs) is presented. A state-of-the-art graphical model for semantic segmentation is extended to incorporate boat pitch and roll measurements from the on-board inertial measurement unit (IMU), and a stereo verification algorithm that consolidates tentative detections obtained from the segmentation is proposed. The IMU readings are used to estimate the location of horizon line in the image, which automatically adjusts the priors in the probabilistic semantic segmentation model. We derive the equations for projecting the horizon into images, propose an efficient optimization algorithm for the extended graphical model, and offer a practical IMU-camera-USV calibration procedure. Using an USV equipped with multiple synchronized sensors, we captured a new challenging multi-modal dataset, and annotated its images with water edge and obstacles. Experimental results show that the proposed algorithm significantly outperforms the state of the art, with nearly 30 % improvement in water-edge detection accuracy, an over 21 % reduction of false positive rate, an almost 60 % reduction of false negative rate, and an over 65 % increase of true positive rate, while its Matlab implementation runs in real-time.
Situation awareness (SA) refers to the awareness of all relevant sources of information, an ability to synthesise this information using domain knowledge gained from past experiences and the ability to physically respond to a situation. Expert-novice differences have been widely reported in decision-making in complex situations although determining the small differences in expert behaviour are more elusive. This study considered how expert squash players use SA to decide on what shot to play. Matches at the 2010 (n = 14) and 2011 (n = 27) Rowe British Grand Prix were recorded and processed using Tracker software. Shot type, ball location, players' positions on court and movement parameters between the time an opponent played a shot prior to the player's shot to the time of the opponent's following shot were captured 25 times per second. Six SA clusters were named to relate to the outcome of a shot ranging from a defensive shot played under pressure to create time to an attempted winner played under no pressure with the opponent out of position. This new methodology found fine-grained SA differences in expert behaviour, even for the same shot type played from the same court area, beyond the usual expert-novice differences.
The physical demands and rally characteristics of elite-standard men's squash have not been well documented since recent rule changes (scoring and tin height). This information is needed to design optimal training drills for physical conditioning provided here based on an analysis of movement and shot information. Matches at the 2010 (n = 14) and 2011 (n = 27) Rowe British Grand Prix were analysed. Rallies were split into four ball-in-play duration categories using the 25th (short), 75th (medium), 95th percentiles (long) and maximum values. Cohen's d and chi-squared tests of independence evaluated effects of rally and rule changes on patterns of play. The proportion of long, middle and short shots was related to the duration of the rally with more shots played in the middle and front of the court in short rallies (phi = 0.12). The frequencies of shots played from different areas of the court have not changed after the adoption of new rules but there is less time available to return shots that reflect the attacking nature of match play for elite-standard men players. Aspiring and current elite-standard players need to condition themselves to improve their ability to cope with these demands using the ghosting patterns presented that mimic demands of modern match play.
We present a novel system for detection, localization and tracking of multiple people, which fuses a multi-view computer vision approach with a radio-based localization system. The proposed fusion combines the best of both worlds, excellent computer-vision-based localization, and strong identity information provided by the radio system, and is therefore able to perform tracking by identification, which makes it impervious to propagated identity switches. We present comprehensive methodology for evaluation of systems that perform person localization in world coordinate system and use it to evaluate the proposed system as well as its components. Experimental results on a challenging indoor dataset, which involves multiple people walking around a realistically cluttered room, confirm that proposed fusion of both systems significantly outperforms its individual components. Compared to the radio-based system, it achieves better localization results, while at the same time it successfully prevents propagation of identity switches that occur in pure computer-vision-based tracking.
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