We propose a novel interest point detector stemming from the intuition that image patches which are highly dissimilar over a relatively large extent of their surroundings hold the property of being repeatable and distinctive. This concept of contextual self-dissimilarity reverses the key paradigm of recent successful techniques such as the Local Self-Similarity descriptor and the Non-Local Mean...

In fields of intelligent robots and computer vision, the capability to select a few points representing salient structures has always been focused and investigated. In this paper, we present a novel interest point detector for 3D range images, which can be used with good results in applications of surface registration and object recognition. A local shape description around each point in the ra...

Article history: Received 23 July 2007 Received in revised form 9 October 2008 Available online 1 November 2008

Is it possible to compare rankings from different sources when the individual rankings of the top x elements differ? To investigate this question, 2015 sustainable rankings from 4 sources that have ranked the top globally most sustainable corporations are considered (Corporate Knights, Fortune’s World’s Most Admired Companies, Newsweek’s Green Rankings, and Harris). These rankings are analyzed ...

In this paper, we introduce BoSP (Bonn Salient Points), a method comprising a pair of a keypoint detector and descriptor in image data that are deeply geared to one another. Our detector identifies points of interest to be local maxima of appearance contrast to their surroundings in a statistical manner. This criterion admits a selection of particularly repeatable, but diverse looking keypoints...

This paper introduces a new operator to characterize a point in an image in a distinctive and invariant way. The robust recognition of points is a key technique in computer vision: algorithms for stereo correspondence, motion tracking and object recognition rely heavily on this type of operator. The goal in this paper is to describe the salient point to be characterized by a constellation of su...

The mouse cerebral cortex was imaged in situ by photoacoustic tomography (PAT). Instead of a flat ultrasonic transducer, a virtual point detector based on a high numerical aperture (NA), positively focused transducer was used. This virtual point detector has a wide omnidirectional acceptance angle, a high sensitivity, and a negligible aperture effect. In addition, the virtual point detector can...

We present an unsupervised 3D deep learning framework based on a ubiquitously true proposition named by us view-object consistency as it states that object and its projected 2D views always belong to the same class. To validate effectiveness, we design multi-view CNN instantiating for salient view selection interest point detection of objects, which quintessentially cannot be handled supervised...

A new method to detect salient pieces of boundaries in an image is presented. After detecting perceptually meaningful level lines, periodic binary sequences are built by labeling each point in close curves as salient or non-salient. We propose a general and automatic method to detect meaningful subsequences within these binary sequences. Experimental results show its good performance.