SEMANTIC SEGMENTATION OF 3D MODEL OBJECTS BASED ON SALIENT POINTS AND CORE EXTRACTION

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MIRLOO MAHSA; EBRAHIMNEZHAD HOSSEIN

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Journal: SIGNAL AND DATA PROCESSING Year:2014 | Volume:- | Issue:1 (SERIAL 21) Page(s): 59-72

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Title

SEMANTIC SEGMENTATION OF 3D MODEL OBJECTS BASED ON SALIENT POINTS AND CORE EXTRACTION

Author(s)

MIRLOO MAHSA | EBRAHIMNEZHAD HOSSEIN | Issue Writer Certificate

Keywords

SEGMENTATIONQ2

3D MODELSQ2

GEODESIC DISTANCEQ2

SALIENT POINTSQ2

CORE EXTRACTIONQ2

Abstract

3D model SEGMENTATION has an important role in 3D model processing programs such as retrieval, compression and watermarking. In this paper, a new 3D model SEGMENTATION algorithm is proposed. Cognitive science research introduces 3D object decomposition as a way of object analysis and detection with human. There are two general types of segments which are obtained from decomposition based on this principle: a core and salient parts. In this approach we start with calculating center of the model. Then, a point with maximum Euclidean distance from the center which represents a prominent part is chosen as the first salient point and its geodesic neighborhood points are deleted from salient point’s search domain. This process is continued until all SALIENT POINTS are detected. Then, the core part which connects the other parts to each other is detected. Thus, 3D model SEGMENTATION is completed. Considering center of the model as the reference point and utilizing both Euclidean and GEODESIC DISTANCE and deleting salient point’s neighborhood from salient point’s search domain led our proposed approach to be invariant against translation, rotation and pose changes and also decrease operation time of the proposed algorithm in comparison with the other 3D model SEGMENTATION algorithms.

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APA: Copy

MIRLOO, MAHSA, & EBRAHIMNEZHAD, HOSSEIN. (2014). SEMANTIC SEGMENTATION OF 3D MODEL OBJECTS BASED ON SALIENT POINTS AND CORE EXTRACTION. SIGNAL AND DATA PROCESSING, -(1 (SERIAL 21)), 59-72. SID. https://sid.ir/paper/160915/en

Vancouver: Copy

MIRLOO MAHSA, EBRAHIMNEZHAD HOSSEIN. SEMANTIC SEGMENTATION OF 3D MODEL OBJECTS BASED ON SALIENT POINTS AND CORE EXTRACTION. SIGNAL AND DATA PROCESSING[Internet]. 2014;-(1 (SERIAL 21)):59-72. Available from: https://sid.ir/paper/160915/en

IEEE: Copy

MAHSA MIRLOO, and HOSSEIN EBRAHIMNEZHAD, “SEMANTIC SEGMENTATION OF 3D MODEL OBJECTS BASED ON SALIENT POINTS AND CORE EXTRACTION,” SIGNAL AND DATA PROCESSING, vol. -, no. 1 (SERIAL 21), pp. 59–72, 2014, [Online]. Available: https://sid.ir/paper/160915/en

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