This paper presents a novel multi scale gradient and a corner point based shape descriptors. The novel multi scale gradient based shape descriptor is combined with generic Fourier descriptors to extract contour and region based shape information. Shape information based object class detection and classification technique with a random forest classifier has been optimized. Proposed integrated de...

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...

With the explosive growth of video capture capable mobile handsets and online visual data repositories, the popular query-by-capture applications call for a compact visual descriptor with minimum descriptor length. How to preserve the visual descriptor information while minimizing the bit rate for representing the descriptors, is a focus of the ongoing MPEG7 CDVS (Compact Descriptor for Visual ...

BACKGROUND We have introduced a new Hybrid descriptor composed of the MACCS key descriptor encoding topological information and Ballester and Richards' Ultrafast Shape Recognition (USR) descriptor. The latter one is calculated from the moments of the distribution of the interatomic distances, and in this work we also included higher moments than in the original implementation. RESULTS The per...

This paper presents a new methodology based on Genetic Programming that aims to create novel mathematical expressions that could improve local descriptors algorithms. We introduce the RDGPILLUM descriptor operator that was learned with two image pairs considering rotation, scale and illumination changes during the training stage. Such descriptor operator has a similar performance to our previou...

Constructing a distinctive and robust sketch descriptor is one of the most challenging problems in sketch based applications. In this paper, a new hand-drawn sketch descriptor is proposed. The proposed descriptor utilizes the statistic information of multiple features and bag-of-features representation to achieve translation and scale invariance and rotation robustness. The proposed descriptor ...

Shape description is one of the key parts of image content description in MPEG-7. Most of existing shape descriptors are usually either application dependent or non-robust, making them undesirable for generic shape description. In this paper, a generic Fourier descriptor (GFD) is proposed to overcome the drawbacks of existing shape representation techniques. The proposed shape descriptor is der...

In this paper, we present a new inductive learning method for multilabel text categorization. The proposed method uses a mutual information measure to select terms and constructs document descriptor vectors for each category based on these terms. These document descriptor vectors form a document descriptor matrix. It also uses the document descriptor vectors to construct a document-similarity m...