Real-time generation of novel views of a dynamic scene using morphing and visual hull

Ishikawa, Takuma; Yamazawa, Kazumasa; Yokoya, Naokazu

doi:10.1109/icip.2005.1529925

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…Chueng et al and Ishikawa et al included their own segmentation methods developed for the visual hull in real environment to their systems [1] [7], but segmentations errors directly affect the visual hull in these systems because the segmentation processes are absolutely independent of reconstruction processes. Grauman et al proposed a Bayesian approach to compensate for modeling errors from false segmentation [3].…”

Section: Introductionmentioning

confidence: 98%

Reliability-based 3D reconstruction in real environment

Kim¹,

Sakamoto²,

Kitahara

et al. 2007

Proceedings of the 15th ACM International Conference on Multimedia

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We present a practical 3D reconstruction method that guarantees robust visual hull construction in real environments where segmentation errors and occlusion exist. The proposed method consists of foreground extraction and reliability-based shapefrom-silhouette, and they are connected by the intra-/intersilhouette reliabilities. In foreground extraction, all regions are classified into four categories based on their intra-reliabilities. Then the reliability-based shape-from-silhouette technique reconstructs a visual hull by carving a 3D space based on the intra-/inter-silhouette reliabilities. The proposed method provides a reliable visual hull in real environments without much increment of the system complexity compared with conventional systems.

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Section: Introductionmentioning

confidence: 98%

Reliability-based 3D reconstruction in real environment

Kim¹,

Sakamoto²,

Kitahara

et al. 2007

Proceedings of the 15th ACM International Conference on Multimedia

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show abstract

“…Chueng et al and Ishikawa et al included their own segmentation methods developed for the visual hull in a real environment to their systems [4,10], but segmentation errors directly affect the visual hull in these systems because the segmentation processes are completely independent of the reconstruction processes.…”

Section: Introductionmentioning

confidence: 98%

“…First, most SFS methods assume perfect silhouette information of objects in advance or use simple background subtraction techniques in restricted environments such as blue screen or simple-colored backgrounds [1,2,3,7,8,10]. Chueng et al and Ishikawa et al included their own segmentation methods developed for the visual hull in a real environment to their systems [4,10], but segmentation errors directly affect the visual hull in these systems because the segmentation processes are completely independent of the reconstruction processes.…”

Section: Introductionmentioning

confidence: 98%

Compensated Visual Hull for Defective Segmentation and Occlusion

Kim¹,

Sakamoto²,

Kitahara

et al. 2007

17th International Conference on Artificial Reality and Telexistence (ICAT 2007)

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We propose an advanced visual hull technique to compensate for outliers using the reliabilities of the silhouettes. The proposed method consists of a foreground extraction technique based on the Generalized Gaussian Family model and a compensated shape-from-silhouette algorithm. They are connected by the intra-/inter-silhouette reliabilities to compensate for carving errors from defective segmentation or partial occlusion which may occur in a real environment. The 3D reconstruction process is implemented on a graphics processing unit (GPU) to accelerate the processing speed by using the huge computational power of modern graphics hardware. Experimental results show that the proposed method provides reliable silhouette information and an accurate visual hull in real environments at a very high speed on a common PC.

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“…Based on a survey provided by Georgios et al [22], state-of-the-art multi-view stereo reconstruction algorithms achieve relative accuracy better than 1/200 (1mm for a 20CM wide object) from a set of low-resolution (640*480) images. They can be classified into 3 methods: (1) visual hull reconstruction algorithms [23,24] can generate full 3D reconstruction of dynamic scenes, but they lack in reconstruction fidelity and are very sensitive to errors in silhouette extraction. (2) Space carving reconstruction methods [25,26] could reconstruct 3D models from multiply images, but they are sensitive to noise and outliers and may yield to noisy reconstructions.…”

Section: Introductionmentioning

confidence: 99%

Accurate, fast, and robust 3D city-scale reconstruction using wide area motion imagery

Yao¹

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Multi-view stereopsis (MVS) is a core problem in computer vision, which takes a set of scene views together with known camera poses, then produces a geometric representation of the underlying 3D model Using 3D reconstruction one can determine any object's 3D profile, as well as knowing the 3D coordinate of any point on the profile. The 3D reconstruction of objects is a generally scientific problem and core technology of a wide variety of fields, such as Computer Aided Geometric Design (CAGD), computer graphics, computer animation, computer vision, medical imaging, computational science, virtual reality, digital media, etc. However, though MVS problems have been studied for decades, many challenges still exist in current state-of-the-art algorithms, for example, many algorithms still lack accuracy and completeness when tested on city-scale large datasets, most MVS algorithms available require a large amount of execution time and/or specialized hardware and software, which results in high cost, and etc... This dissertation work tries to address all the challenges we mentioned, and proposed multiple solutions. More specifically, this dissertation work proposed multiple novel MVS algorithms to automatically and accurately reconstruct the underlying 3D scenes. By proposing a novel volumetric voxel-based method, one of our algorithms achieved near real-time runtime speed, which does not require any special hardware or software, and can be deployed onto power-constrained embedded systems. By developing a new camera clustering module and a novel weighted voting-based surface likelihood estimation module, our algorithm is generalized to process di erent datasets, and achieved the best performance in terms of accuracy and completeness when compared with existing algorithms. This dissertation work also performs the very first quantitative evaluation in terms of precision, recall, and F-score using real-world LiDAR groundtruth data. Last but not least, this dissertation work proposes an automatic workflow, which can stitch multiple point cloud models with limited overlapping areas into one larger 3D model for better geographical coverage. All the results presented in this dissertation work have been evaluated in our wide area motion imagery (WAMI) dataset, and improved the state-of-the-art performances by a large margin.The generated results from this dissertation work have been successfully used in many aspects, including: city digitization, improving detection and tracking performances, real time dynamic shadow detection, 3D change detection, visibility map generating, VR environment, and visualization combined with other information, such as building footprint and roads.

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Real-time generation of novel views of a dynamic scene using morphing and visual hull

Cited by 6 publications

References 9 publications

Reliability-based 3D reconstruction in real environment

Reliability-based 3D reconstruction in real environment

Compensated Visual Hull for Defective Segmentation and Occlusion

Accurate, fast, and robust 3D city-scale reconstruction using wide area motion imagery

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