Shape from shading with a generalized reflectance map model
Computer Vision and Image Understanding
Spatial Color Indexing and Applications
International Journal of Computer Vision
A Comparison of Shape Retrieval Using Fourier Descriptors and Short-Time Fourier Descriptors
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Content-based image retrieval: approaches and trends of the new age
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Invariant salient regions based image retrieval under viewpoint and illumination variations
Journal of Visual Communication and Image Representation
Kernel-based distance metric learning for content-based image retrieval
Image and Vision Computing
Combining color and shape information for illumination-viewpoint invariant object recognition
IEEE Transactions on Image Processing
Interaction techniques for integrated content-based enterprise search
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part III
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Content based image retrieval (CBIR), a technique which uses visual contents to search images from the large scale image databases, is an active area of research for the past decade. It is increasingly evident that an image retrieval system has to be domain specific. In this paper, we present an algorithm for retrieving images with respect to a database consisting of engineering/computer-aided design (CAD) models. The algorithm uses the shape information in an image along with its 3D information. A linear approximation procedure that can capture the depth information using the idea of shape from shading has been used. Retrieval of objects is then done using a similarity measure that combines shape and the depth information. Plotted precision/recall curves show that this method is very effective for an engineering database.