Visual odometry has been used in many fields, especially in robotics and intelligent vehicles. Since local descriptors are robust to background clutter, occlusion and other content variations, they have been receiving more and more attention in the application of the detector-descriptor based visual odometry. To our knowledge, however, there is no extensive, comparative evaluation investigating...

In image retrieval, global features related to color or texture are commonly used to describe the image content. The problem with this approach is that these global features cannot capture all parts of the image having different characteristics. Therefore, local computation of image information is necessary. By using salient points to represent local information, more discriminative features ca...

This paper investigates the coincidence between six interest point detection methods (SIFT, MSER, Harris-Laplace, SURF, FAST & Kadir-Brady Saliency) with two robust “bottom-up” models of visual saliency (Itti and Harel) as well as “task” salient surfaces derived from observer eye-tracking data. Comprehensive statistics for all detectors vs. saliency models are presented in the presence and abse...

This paper proposes a detector for spatio-temporal interest points. Interest point detection is a common technique in computer vision to extract salient regions and represent them by a single point for further processing. But while many algorithms exist for static images, there is hardly any method to obtain interest points from image sequences for the representation of salient motion. Here we ...

In image retrieval, global features related to color or texture are commonly used to describe the image. The use of interest points in contentbased image retrieval allows image index to represent local properties of images. Classic corner detectors can be used for this purpose. However, they have drawbacks when applied to various natural images for image retrieval, because visual features need ...

We present a new method for the detection of 3D keypoints on point clouds and we perform benchmarking between each pair of 3D keypoint detector and 3D descriptor to evaluate their performance on object and category recognition. Our keypoint detector is inspired by the behavior and neural architecture of the primate visual system. The 3D keypoints are extracted based on a bottom-up 3D saliency m...

Purpose – This paper aims to present a novel feature design that is able to precisely describe salient objects in images. With the development of space survey, sensor and information acquisition technologies, more complex objects appear in high-resolution remote sensing images. Traditional visual features are no longer precise enough to describe the images. Design/methodology/approach – A novel...

Here we present a novel, histogram-based salient point feature detector that may naturally be applied to both images and 3D data. Existing point feature detectors are often modality specific, with 2D and 3D feature detectors typically constructed in separate ways. As such, their applicability in a 2D-3D context is very limited, particularly where the 3D data is obtained by a LiDAR scanner. By c...