Semantics of immersive web through its architectural structure and graphic primitives

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To this day, digital object reconstruction is a quite complex area that requires many techniques and novel approaches, in which high-resolution 3D objects present one of the biggest challenges. There are mainly two different methods that can be used to reconstruct high resolution objects and images: passive methods and active methods. This methods depend on the type of information available as input for modeling 3D objects. The passive methods use information contained in the images and the active methods make use of controlled light sources, such as lasers. The reconstruction of 3D objects is quite complex and there is no unique solution-The use of specific methodologies for the reconstruction of certain objects it's also very common, such as human faces, molecular structures, etc. This paper proposes a novel hybrid methodology, composed by 10 phases that combine active and passive methods, using images and a laser in order to supplement the missing information and obtain better results in the 3D object reconstruction. Finally, the proposed methodology proved its efficiency in two complex topological complex objects Keywords-Visual hull, octree, ICP (iterative closest point), marching cubes, iso-surface, iso-level.

Section: ) Phase 10: Texture Mappingmentioning

confidence: 99%

Reconstruction of High Resolution 3D Objects from Incomplete Images and 3D Information

Pacheco¹,

Bolívar²,

Espada³

et al. 2014

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“…Our major concern is that the image should not show any visual effects and it carries as much data as possible. Some other approaches can also be utilized with to enhance the algorithm [2][3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Robust Lossless Semi Fragile Information Protection in Images

Dixit¹,

Singh²,

Gupta³

2014

Internet security finds it difficult to keep the information secure and to maintain the integrity of the data. Sending messages over the internet secretly is one of the major tasks as it is widely used for passing the message. In order to achieve security there must be some mechanism to protect the data against unauthorized access. A lossless data hiding scheme is proposed in this paper which has a higher embedding capacity than other schemes. Unlike other schemes that are used for embedding fixed amount of data, the proposed data hiding method is block based approach and it uses a variable data embedding in different blocks which reduces the chances of distortion and increases the hiding capacity of the image. When the data is recovered the original image can be restored without any distortion. Our experimental results indicate that the proposed solution can significantly support the data hiding problem. We achieved good Peak signal-to-noise ratio (PSNR) while hiding large amount of data into smoother regions.

“…But, there method requires multiple cameras from different viewpoints to model multi-view recognition system which requires extra setup and also computation, whereas the proposed approach is able to achieve high recognition performance from only a single viewpoint. Several other approaches and features used in [13][14][15][16][17][18][19][20][21][22][23][24][25] may be tied with gait analysis to predict the human actions. Human activity recognition using smartphones is also studied [26] but its recognition rate can be improved using gait analysis with more time efficiently.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Gait Pattern to Recognize the Human Activities

Gupta¹,

Dixit²,

Semwal³

2014

-Human activity recognition based on the computer vision is the process of labelling image sequences with action labels. Accurate systems for this problem are applied in areas such as visual surveillance, human computer interaction and video retrieval. The challenges are due to variations in motion, recording settings and gait differences. Here we propose an approach to recognize the human activities through gait. Activity recognition through Gait is the process of identifying an activity by the manner in which they walk. The identification of human activities in a video, such as a person is walking, running, jumping, jogging etc are important activities in video surveillance. We contribute the use of Model based approach for activity recognition with the help of movement of legs only. Experimental results suggest that our method are able to recognize the human activities with a good accuracy rate and robust to shadows present in the videos.