199 resultados para camera motion


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The selection of optimal camera configurations (camera locations, orientations etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we introduce a statistical formulation of the optimal selection of camera configurations as well as propose a Trans-Dimensional Simulated Annealing (TDSA) algorithm to effectively solve the problem. We compare our approach with a state-of-the-art method based on Binary Integer Programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than 2 alternative heuristics designed to deal with the scalability issue of BIP.

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Background: Measurement accuracy is critical for biomechanical gait assessment. Very few studies have determined the accuracy of common clinical rearfoot variables between cameras with different collection frequencies. Research question: What is the measurement error for common rearfoot gait parameters when using a standard 30Hz digital camera compared to 100Hz camera? Type of study: Descriptive. Methods: 100 footfalls were recorded from 10 subjects ( 10 footfalls per subject) running on a treadmill at 2.68m/s. A high-speed digital timer, accurate within 1ms served as an external reference. Markers were placed along the vertical axis of the heel counter and the long axis of the shank. 2D coordinates for the four markers were determined from heel strike to heel lift. Variables of interest included time of heel strike (THS), time of heel lift (THL), time to maximum eversion (TMax), and maximum rearfoot eversion angle (EvMax). Results: THS difference was 29.77ms (+/- 8.77), THL difference was 35.64ms (+/- 6.85), and TMax difference was 16.50ms (+/- 2.54). These temporal values represent a difference equal to 11.9%, 14.3%, and 6.6% of the stance phase of running gait, respectively. EvMax difference was 1.02 degrees (+/- 0.46). Conclusions: A 30Hz camera is accurate, compared to a high-frequency camera, in determining TMax and EvMax during a clinical gait analysis. However, relatively large differences, in excess of 12% of the stance phase of gait, for THS and THL variables were measured.

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Purpose: To examine the relationship between hip abductor muscle (HABD) strength and the magnitude of pelvic drop (MPD) for patients with non-specific low back pain (NSLBP) and controls (CON) prior to and following a 3-week HABD strengthening protocol. At baseline, we hypothesized that NSLBP patients would exhibit reduced HABD strength and greater MPD compared to CON. Following the protocol, we hypothesized that strength would increase and MPD would decrease. Relevance: The Trendelenburg test (TT) is a common clinical test used to examine the ability of the HABD to maintain horizontal pelvic position during single limb stance. However, no study has specifically tested this theory. Moreover, no study has investigated the relationship between HABD strength and pelvic motion during walking or tested whether increased HABD strength would reduce the MPD. Methods: Quasi-experimental with 3-week exercise intervention. Fifteen NSLBP patients (32.5yrs,range 21-51yrs; VAS baseline: 5.3cm) and 10 CON (29.5yrs,range 22-47yrs) were recruited. Isometric HABD strength was measured using a force dynamometer and the average of three maximal voluntary contractions were normalized to body mass (N/kg). Two-dimensional MPD (degrees) was measured using a 60 Hz camera and was derived from two retroreflective-markers placed on the posterior superior iliac spines. MPD was measured while performing the static TT and while walking and averaged over 10 consecutive footfalls. NSLBP patients completed a 3-week HABD strengthening protocol consisting of 2 open-kinetic-chain exercises then all measures were repeated. Non-parametric analysis was used for group comparisons and correlation analysis. Results: At baseline, the NSLBP patients demonstrated 31% reduced HABD strength (mean=6.6 N/kg) compared to CON (mean=9.5 N/kg: p=0.03) and no significant differences in maximal pelvic frontal plane excursion while walking (NSLBP:mean=8.1°, CON:mean=7.1°: p=0.72). No significant correlations were measured between left HABD strength and right MPD (r=-0.37, p=0.11), or between right HABD strength and left MPD (r=-0.04, p=0.84) while performing the static TT. Following the 3-week strengthening protocol, NSLBP patients demonstrated a 12% improvement in strength (Post:mean=7.4 N/kg: p=0.02), a reduction in pain (VAS followup: 2.8cm), but no significant decreases in MPD while walking (p=0.92). Conclusions: NSLBP patients demonstrated reduced HABD strength at baseline and were able to increase strength and reduce pain in a 3-week period. However, despite increases in HABD strength, the NSLBP group exhibited similar MPD motion during the static TT and while walking compared to baseline and controls. Implications: The results suggest that the HABD alone may not be primarily responsible for controlling a horizontal pelvic position during static and dynamic conditions. Increasing the strength of the hip abductors resulted in a reduction of pain in NSLBP patients providing evidence for further research to identify specific musculature responsible for controlling pelvic motion.

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The building sector is the dominant consumer of energy and therefore a major contributor to anthropomorphic climate change. The rapid generation of photorealistic, 3D environment models with incorporated surface temperature data has the potential to improve thermographic monitoring of building energy efficiency. In pursuit of this goal, we propose a system which combines a range sensor with a thermal-infrared camera. Our proposed system can generate dense 3D models of environments with both appearance and temperature information, and is the first such system to be developed using a low-cost RGB-D camera. The proposed pipeline processes depth maps successively, forming an ongoing pose estimate of the depth camera and optimizing a voxel occupancy map. Voxels are assigned 4 channels representing estimates of their true RGB and thermal-infrared intensity values. Poses corresponding to each RGB and thermal-infrared image are estimated through a combination of timestamp-based interpolation and a pre-determined knowledge of the extrinsic calibration of the system. Raycasting is then used to color the voxels to represent both visual appearance using RGB, and an estimate of the surface temperature. The output of the system is a dense 3D model which can simultaneously represent both RGB and thermal-infrared data using one of two alternative representation schemes. Experimental results demonstrate that the system is capable of accurately mapping difficult environments, even in complete darkness.

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In this paper we demonstrate passive vision-based localization in environments more than two orders of magnitude darker than the current benchmark using a 100 webcam and a 500 camera. Our approach uses the camera’s maximum exposure duration and sensor gain to achieve appropriately exposed images even in unlit night-time environments, albeit with extreme levels of motion blur. Using the SeqSLAM algorithm, we first evaluate the effect of variable motion blur caused by simulated exposures of 132 ms to 10000 ms duration on localization performance. We then use actual long exposure camera datasets to demonstrate day-night localization in two different environments. Finally we perform a statistical analysis that compares the baseline performance of matching unprocessed greyscale images to using patch normalization and local neighbourhood normalization – the two key SeqSLAM components. Our results and analysis show for the first time why the SeqSLAM algorithm is effective, and demonstrate the potential for cheap camera-based localization systems that function across extreme perceptual change.

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This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.

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This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.

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The emergence of shopping malls in Europe, the UK and Australia over the last thirty years or so, raises questions about the disruptive effects of such capital intensive developments on local area shopping facilities, transport and other infrastructures and the maintenance of artificially high prices for goods, whereby the promised greater choice of shops and prices is rarely a genuine free market of competition leading to lower prices. A central question to be addressed is whom these centres represent and belong to. While many claim to exist to ‘serve the community’ almost all malls and centres are private property and the community of shoppers has few, if any rights compared with the conventional high street, which is a public thoroughfare. This permits the management of the centres through their own private security staff, to observe, follow, eject and refuse further admission to anyone considered to be ‘undesirable’. What is different about the newest shopping centres is the routine use of increasingly sophisticated CCTV surveillance equipment to observe and record, for later evidential and entry restriction use, the movements of centre visitors.

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Distal radius fractures stabilized by open reduction internal fixation (ORIF) have become increasingly common. There is currently no consensus on the optimal time to commence range of motion (ROM) exercises post-ORIF. A retrospective cohort review was conducted over a five-year period to compare wrist and forearm range of motion outcomes and number of therapy sessions between patients who commenced active ROM exercises within the first seven days and from day eight onward following ORIF of distal radius fractures. One hundred and twenty-one patient cases were identified. Clinical data, active ROM at initial and discharge therapy assessments, fracture type, surgical approaches, and number of therapy sessions attended were recorded. One hundred and seven (88.4%) cases had complete datasets. The early active ROM group (n = 37) commenced ROM a mean (SD) of 4.27 (1.8) days post-ORIF. The comparator group (n = 70) commenced ROM exercises 24.3 (13.6) days post-ORIF. No significant differences were identified between groups in ROM at initial or discharge assessments, or therapy sessions attended. The results from this study indicate that patients who commenced active ROM exercises an average of 24 days after surgery achieved comparable ROM outcomes with similar number of therapy sessions to those who commenced ROM exercises within the first week.

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This paper proposes a practical prediction procedure for vertical displacement of a Rotarywing Unmanned Aerial Vehicle (RUAV) landing deck in the presence of stochastic sea state disturbances. A proper time series model tending to capture characteristics of the dynamic relationship between an observer and a landing deck is constructed, with model orders determined by a novel principle based on Bayes Information Criterion (BIC) and coefficients identified using the Forgetting Factor Recursive Least Square (FFRLS) method. In addition, a fast-converging online multi-step predictor is developed, which can be implemented more rapidly than the Auto-Regressive (AR) predictor as it requires less memory allocations when updating coefficients. Simulation results demonstrate that the proposed prediction approach exhibits satisfactory prediction performance, making it suitable for integration into ship-helicopter approach and landing guidance systems in consideration of computational capacity of the flight computer.

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Motion capture continues to be adopted across a range of creative fields including, animation, games, visual effects, dance, live theatre and the visual arts. This panel will discuss and showcase the use of motion capture across these creative fields and consider the future of virtual production in the creative industries.

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Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.

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This article is a call to literacy teachers and researchers to embrace the possibility of attending more consciously to the senses in digital media production. Literacy practices do not occur only in the mind, but involve the sensoriality, embodiment, co-presence, and movement of bodies. This paper theorises the sensorial and embodied dimension of children’s filmmaking about place in two communities in Australia. The films were created by pre-teen Indigenous and non-Indigenous children in Logan, Queensland, and by Indigenous teenagers at the Warralong campus of the Strelley Community School in remote Western Australia. The films were created through engagement in cross-curricular units that sensitised the students’ experience of local places, gathering corporeal information through their sensing bodies as they interacted with the local ecology. The analysis highlights how the sensorial and bodily nature of literacy practice through documentary filmmaking was central to the children’s formation and representation of knowledge, because knowledge and literacy practices are not only acquired through the mind, but are also reliant on embodiment, sensoriality, co-presence, and kinesics of the body in place.

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A multi-segment foot model was used to develop an accurate and reliable kinematic model to describe in-shoe foot kinematics during gait.

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In the movie industry, the extraordinarily successful theatrical performance of certain films is largely attributed to buzz. Despite longstanding commentary about the role of buzz in successful movie marketing and the belief that it accelerates new product diffusion, limited scholarly evidence exists to support these assertions. This is primarily due to the lack of conceptual distinction of buzz from word-of-mouth, which is often used as the main basis for conceptualising buzz. However, word-of-mouth does not fully explain the buzz surrounding films such as 'Gone With The Wind', 'The Dark Knight' and 'Avatar'. Informed by valuable insights from key experts who have launched some of the most successful movies in box office history, as well as a range of moviegoers, this thesis developed a deeper understanding of what buzz is and how it is created. This thesis concludes that buzz is not the same as word-of-mouth.