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techniques to describe a scene in a structural way, in contrast to traditional waveform-based coding techniques, opens new areas of applications. Video production, realistic computer graphics, multimedia interfaces and medical visualization are some of the applications that may benefit by exploiting the potential of object based schemes. Object-based approaches applied in coding of stereo image sequences have the additional benefit of conveying depth information which may be computed directly from the images. Using the depth information the scene may be separated in layers and depth keying is possible. Also, accurate 3D modeling of the scene structure may be achieved. The main problem in object based analysis is the automatic extraction and modeling of objects directly from the image intensities. This task
MSO4 Input
Motion & Structure estimation
Segmentation
Object parameter coding
Ch4
Image synthesis
SycO4 M1 M2 Error coding M3
Object-Based Stereoscopic Video Coding. Figure 1. General structure of an object-based stereo coding scheme.
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Object Recognition
may require complex image analysis techniques to segment the scene into homogeneous regions or even user interaction so that image regions correspond to real objects on the scene. Figure 1 illustrates the basic structure of an objectbased stereoscopic image coding scheme. The encoder consists of an analysis part and a synthesis part. The analysis part aims to subdivide the scene into a set of objects representing each one by a set of parameters: shape or boundary, motion, structure or depth and texture or color. These parameters are encoded and transmitted to the decoder where the decoded parameters are then used to synthesize an approximation of the original images. The analysis phase is the most sophisticated one, consisting of image segmentation and motion/structure estimation.
Cross-References ▶ Coding of Stereoscopic and 3D Images and Video
References 1.
M.G. Strintzis and S. Malassiotis: ‘‘Object-Based Coding of Stereoscopic and 3D Image Sequences: A Review,’’ IEEE Signal Processing Magazine, Special Issue on Stereo and 3D Imaging (invited paper), Vol. 16, No. 3, May 1999, pp. 14–28.
Object Recognition ▶ Detection of High-Level Concepts in Multimedia
Object Recognition and Pose Estimation from 2.5D Scenes G. KORDELAS , A. M ADEMLIS , P. DARAS , M. G. S TRINTZIS Aristotle University of Thessaloniki, Thessaloniki, Greece
Synonyms ▶ Identification of objects and retrieval of their pose
Definition 3D Object recognition is a computer vision’s research topic which aims at recognizing objects from 2.5D data
range images and estimating their positions and orientations. The challenge of recognizing objects and estimating their pose (position and orientation) has been addressed in several ways. The most well-known approaches that have been presented so far try to solve this problem by acquiring 2D training image sequences that describe the objects’ visual appearance from different viewpoints and extracting features from them. Afterwards, for
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