While 3D object representations are being revived in the context of multi-view object class
detection and scene understanding, they have not yet attained wide-spread use in fine …

Highlights•We propose a color agnostic fruit detection scheme for precision agriculture
tasks.•We reply on registered image (RGB) and depth (range data), aka RGB-D images.•We …

Nearest neighbor search is a fundamental problem in various domains, such as computer
vision, data mining, and machine learning. With the explosive growth of data on the Internet …

Multipath interference of light is the cause of important errors in Time of Flight (ToF) depth
estimation. This paper proposes an algorithm that removes multipath distortion from a single …

Object representation based on local features is a topical subject in the domain of image
understanding and computer vision. We discuss the defects of global features in present …

This paper studies the problem of RGB-D object recognition. Inspired by the great success of
deep convolutional neural networks (DCNN) in AI, researchers have tried to apply it to …

Object recognition in real-world environments is one of the fundamental and key tasks in
computer vision and robotics communities. With the advanced sensing technologies and low …

In this paper, we present an active SLAM framework for volumetric exploration of 3D
underwater environments with multibeam sonar. Recent work in integrated SLAM and …

Fine-grained recognition concerns categorization at sub-ordinate levels, where the
distinction between object classes is highly local. Compared to basic level recognition, fine …

Human hand gesture recognition is important to Human-Computer-Interaction. Gesture
recognition based on RGB-D data exploits both RGB and depth images to provide …