A Review of Dynamic Motion Control Considering Physics for Real Time Animation Character

Ismail, Ismahafezi; Sunar, Mohd Shahrizal; Sidik, Mohd Kufaisal Mohd; Yusof, Cik Suhaimi

doi:10.1109/dmdcm.2011.25

Cited by 4 publications

(1 citation statement)

References 26 publications

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“…Isenberg [8], in 2003, classified all silhouette detection techniques in three groups, image space algorithms which focus on image processing , the second group is object space algorithms which are divided in two groups, free form and polygon mesh and final group is hybrid algorithms. In compare by finding accuracy silhouette and appropriate stylization the second group algorithms are better than the [9,10,16].…”

Section: Previous Workmentioning

confidence: 94%

Hybrid Silhouette Detection for Real-Time Shadow Volume

Kolivand¹,

Sunar²

2011

IJVR

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In shadow volume, the most expensive computation is silhouette detection. In this paper, the triangular algorithm (TA) and visible-non-visible (VnV) algorithm that are famous algorithms to detect the outline of occluder are renewed. In this paper, we proposed a hybrid algorithm based on TA and VnV, namely Hybrid Silhouette Detection (HSD) algorithm. HSD is an improved algorithm that can recognize silhouette for generating real-time shadow volume. Our algorithm involves detecting silhouette and decreases the cost of implementation for shadow volume rendering. The last shadow volume algorithm using stencil buffer is rewritten and an algorithm for shadow volume using HSD with respect of culling invisible parts of scene is proposed. An accurate mathematical comparison between TA, VnV and HSD algorithms is undertaken. The obtained results confirm superiority of our proposed algorithm in terms of processing and rendering time. Our algorithm can be used in virtual environment to increase the frame

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Section: Previous Workmentioning

confidence: 94%

Hybrid Silhouette Detection for Real-Time Shadow Volume

Kolivand¹,

Sunar²

2011

IJVR

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A Study on Natural Interaction for Human Body Motion Using Depth Image Data

Sidik

Sunar²,

Ismail³

et al. 2011

2011 Workshop on Digital Media and Digital Content Management

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Method of Registration for 3d Face Point Cloud Data

2015

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This paper analyzes the techniques that can be used to perform point cloud data registration for a human face. We found that there is a limitation in full scale viewing on the input data taken from 3D camera which is only represented the front face of a man as the point of view of a camera. This has caused a hole on the surface that is not filled with the point cloud data. This research is done by mapping the retrieved point cloud to the surface of the face template of the human head. By using Coherent Point Drift (CPD) algorithm which is one of the non-rigid registration techniques, the analysis has been done and it shows that the mapping of points for a three-dimensional (3D) face is not done properly where there are some surfaces work well and certain points spread into the wrong area. Consequently, it has resulted in registration failure occurrences due to the concentration of the points which is focusing on the face only.

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A Review of Dynamic Motion Control Considering Physics for Real Time Animation Character

Cited by 4 publications

References 26 publications

Hybrid Silhouette Detection for Real-Time Shadow Volume

Hybrid Silhouette Detection for Real-Time Shadow Volume

A Study on Natural Interaction for Human Body Motion Using Depth Image Data

Method of Registration for 3d Face Point Cloud Data

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