3D scanning of cultural heritage with consumer depth cameras

Three dimensional reconstruction of cultural heritage objects is an expensive and time-consuming process. Recent consumer real-time depth acquisition devices, like Microsoft Kinect, allow very fast and simple acquisition of 3D views. However 3D scanning with such devices is a challenging task due to the limited accuracy and reliability of the acquired data. This paper introduces a 3D reconstruction pipeline suited to use consumer depth cameras as hand-held scanners for cultural heritage objects. Several new contributions have been made to achieve this result. They include an ad-hoc filtering scheme that exploits the model of the error on the acquired data and a novel algorithm for the extraction of salient points exploiting both depth and color data. Then the salient points are used within a modified version of the ICP algorithm that exploits both geometry and color distances to precisely align the views even when geometry information is not sufficient to constrain the registration. The proposed method, although applicable to generic scenes, has been tuned to the acquisition of sculptures and in this connection its performance is rather interesting as the experimental results indicate

Airborne photogrammetry and LIDAR for DSM extraction and 3D change detection over an urban area : a comparative study

A digital surface model (DSM) extracted from stereoscopic aerial images, acquired in March 2000, is compared with a DSM derived from airborne light detection and ranging (lidar) data collected in July 2009. Three densely built-up study areas in the city centre of Ghent, Belgium, are selected, each covering approximately 0.4 km(2). The surface models, generated from the two different 3D acquisition methods, are compared qualitatively and quantitatively as to what extent they are suitable in modelling an urban environment, in particular for the 3D reconstruction of buildings. Then the data sets, which are acquired at two different epochs t(1) and t(2), are investigated as to what extent 3D (building) changes can be detected and modelled over the time interval. A difference model, generated by pixel-wise subtracting of both DSMs, indicates changes in elevation. Filters are proposed to differentiate 'real' building changes from false alarms provoked by model noise, outliers, vegetation, etc. A final 3D building change model maps all destructed and newly constructed buildings within the time interval t(2) - t(1). Based on the change model, the surface and volume of the building changes can be quantified

Initial experience using contrast enhanced real-time three-dimensional exercise stress echocardiography in a low-risk population

Although emerging data support the utility of real-time three-dimensional echocardiography (RT3DE) during dobutamine stress testing, the feasibility of performing contrast enhanced RT3DE during exercise treadmill stress has not been explored. Two-dimensional (2D) and three-dimensional (3D) acquisition were performed in 39 patients at rest and peak exercise. Contrast was used in 29 patients (74%). Reconstruction was performed manually by generating short axis cut planes at the base, mid-ventricle and apex, and automatically by generating 9 short axis slices. Three-dimensional acquisition was feasible during rest and stress regardless of the use of contrast. Time to acquire stress images was reduced using 3D (35.2±17.9 s) as compared to 2D acquisition (51.6±14.7 s; P<0.05). Using a 17-segment model, of all 663 segments, 588 resting (88.6%) and 563 stress segments (84.9%) were adequately visualized using manually reconstructed 3D data, compared with 618 resting (93.2%) and 606 stress segments (91.4%) using 2D data (P rest=0.06; P stress=0.07). We concluded that contrast enhanced RT3DE is feasible during treadmill stress echocardiography

Reconstruction of the 3D Object Model: A review

The three-dimensional (3D) reconstruction model of a real object is useful in many applications ranging from medical imaging, product design, parts inspection, reverse engineering to rapid prototyping. In the medical field, imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI) and single positron emission tomography (SPECT) are applied to create 3D images from emanation measurements for disease diagnoses and organ study. On the other hand, reconstruction is widely utilized to redesign manufacturing parts in order to save production cost and time. A typical reconstruction application consists of three major steps, which are data acquisition, registration and integration as well as surface fitting. Based on the nature of data captured, the 3D reconstruction model can be categorized into two groups: methods working on (i) two-dimensional (2D) images and (ii) sets of 3D points. This paper reviews different methods of 3D object model reconstruction and techniques subjected to each method

Designing 3D selection techniques using ballistic and corrective movements

The two-component model is a human movement model in which an aimed movement is broken into a voluntary ballistic movement followed by a corrective movement. Recently, experimental evidence has shown that 3D aimed movements in virtual environments can be modeled using the two-component model. In this paper, we use the two-component model for designing 3D interaction techniques which aim at facilitating pointing tasks in virtual reality. This is achieved by parsing the 3D aimed movement in real time into the ballistic and corrective phases, and reducing the index of difficulty of the task during the corrective phase. We implemented two pointing techniques. The 'AutoWidth' technique increases the target width during the corrective phase and the 'AutoDistance' technique decreases the distance to the target at the end of ballistic phase. We experimentally demonstrated the benefit of these techniques by comparing them with freehand aimed movements. It was shown that both 'AutoWidth' and 'AutoDistance' techniques exhibit significant improvement on target acquisition time

Designing 3D Selection Techniques Using Ballistic and Corrective Movements

The two-component model is a human movement model in which an aimed movement is broken into a voluntary ballistic movement followed by a corrective movement. Recently, experimental evidence has shown that 3D aimed movements in virtual environments can be modeled using the two-component model. In this paper, we use the two-component model for designing 3D interaction techniques which aim at facilitating pointing tasks in virtual reality. This is achieved by parsing the 3D aimed movement in real time into the ballistic and corrective phases, and reducing the index of difficulty of the task during the corrective phase. We implemented two pointing techniques. The ‘AutoWidth’ technique increases the target width during the corrective phase and the ‘AutoDistance’ technique decreases the distance to the target at the end of ballistic phase. We experimentally demonstrated the benefit of these techniques by comparing them with freehand aimed movements. It was shown that both ‘AutoWidth’ and ‘AutoDistance’ techniques exhibit significant improvement on target acquisition time

Marker-less Real Time 3D Modeling for Virtual Reality

International audienceToday, immersive environments mainly use a few 3D positions given by trackers to align the real and virtual worlds. In this paper we present an alternative approach using commodity components to achieve real time marker-less 3D modeling in virtual reality environments. The goal is to compute in real time a 3D shape of the objects and users present in the interaction space without having to equip them with markers. Having full 3D shapes opens new possibilities for full-body interactions and a tight virtual/real world integration. Data acquisition is performed through cameras surrounding the interaction space. A visual hull reconstruction algorithm is parallelized on a PC cluster to compute in real time the 3D shapes of the scene observed. Experimental results using 4 cameras and 20 processors lead to a precise 3D human model built in real time

Markerless Real Time 3D Modeling for Virtual Reality

Abstract Today, immersive environments mainly use a few 3D positions given by trackers to align the real and virtual worlds. In this paper we present an alternative approach using commodity components to achieve real time marker-less 3D modeling in virtual reality environments. The goal is to compute in real time a 3D shape of the objects and users present in the interaction space without having to equip them with markers. Having full 3D shapes opens new possibilities for full-body interactions and a tight virtual/real world integration. Data acquisition is performed through cameras surrounding the interaction space. A visual hull reconstruction algorithm is parallelized on a PC cluster to compute in real time the 3D shapes of the scene observed. Experimental results using 4 cameras and 20 processors lead to a precise 3D human model built in real time

Real-time multi-directional flow MRI using model-based reconstructions of undersampled radial FLASH – A feasibility study

The purpose of this work was to develop an acquisition and reconstruction technique for two- and three-directional (2d and 3d) phase-contrast flow MRI in real time. A previous real-time MRI technique for one-directional (1d) through-plane flow was extended to 2d and 3d flow MRI by introducing in-plane flow sensitivity. The method employs highly undersampled radial FLASH sequences with sequential acquisitions of two or three flow-encoding datasets and one flow-compensated dataset. Echo times are minimized by merging the waveforms of flow-encoding and radial imaging gradients. For each velocity direction individually, model-based reconstructions by regularized nonlinear inversion jointly estimate an anatomical image, a set of coil sensitivities and a phase-contrast velocity map directly. The reconstructions take advantage of a dynamic phase reference obtained by interpolating consecutive flow-compensated acquisitions. Validations include pulsatile flow phantoms as well as in vivo studies of the human aorta at 3 T. The proposed method offers cross-sectional 2d and 3d flow MRI of the human aortic arch at 53 and 67 ms resolution, respectively, without ECG synchronization and during free breathing. The in-plane resolution was 1.5 × 1.5 mm2 and the slice thickness 6 mm. In conclusion, real-time multi-directional flow MRI offers new opportunities to study complex human blood flow without the risk of combining differential phase (i.e., velocity) information from multiple heartbeats as for ECG-gated data. The method would benefit from a further reduction of acquisition time and accelerated computing to allow for extended clinical trials