This paper presents work in progress to extend the two-dimensional (2D) Scale Invariant Feature Transform (SIFT) to a 2.5 dimensional (2.5D) domain. Robust feature descriptors are extracted from range images of human faces and the form of these descriptors are analogous to the structure of Lowe’s 2D SIFT, in which the descriptors comprise a local distribution function of the image gradient orie...

In this paper, we propose a novel 3D free form surface matching method based on a novel key-point detector and a novel feature descriptor. The proposed detector is based on algebraic surface fitting. By global smooth fitting, our detector achieved high computational efficiency and robustness against non-rigid deformations. For the feature descriptor, we provide algorithms to compute 3D critical...

In this paper, a new texture descriptor based on the local neighborhood intensity difference is proposed for content based image retrieval (CBIR). For computation of texture features like Local Binary Pattern (LBP), the center pixel in a 3×3 window of an image is compared with all the remaining neighbors, one pixel at a time to generate a binary bit pattern. It ignores the effect of the adjacen...

Feature-driven analysis forms the basis of many shape processing tasks, where detected feature points are characterized by local shape descriptors. Such descriptors have so far been defined to capture regions of interest centered at individual points. Using such regions to compare feature points can be problematic when performing partial shape matching, since the region of interest is typically...

A new method to describe sperm vitality using a hybrid combination of local and global texture descriptors is proposed in this paper. In this regard, a new adaptive local binary pattern (ALBP) descriptor is presented in order to carry out the local description. It is built by adding oriented standard deviation information to an ALBP descriptor in order to achieve a more complete representation ...

A very simple but efficient feature descriptor is proposed for image matching/registration applications where invariance is not important. The descriptor length is only three times the height of the local region in which the descriptor is calculated, and experiments were conducted to compare it to the SURF descriptor. In addition, it is shown, how the sampling can be modified in order to obtain...

The paper presents an efficient and reliable feature descriptor for human detection in a top-view depth image that uses two statistical values of mean and standard deviation. Human detection performance of our descriptor outperform Rauter that use mean value and Simplified Local Ternary Pattern (SLTP). To evaluate the human detection performance using our descriptor, we capture 559 positive and...