Revisiting Digital Straight Segment Recognition

This paper presents new results about digital straight segments, their recognition and related properties. They come from the study of the arithmetically based recognition algorithm proposed by I. Debled-Rennesson and J.-P. Reveill\`es in 1995 [Debled95]. We indeed exhibit the relations describing the possible changes in the parameters of the digital straight segment under investigation. This description is achieved by considering new parameters on digital segments: instead of their arithmetic description, we examine the parameters related to their combinatoric description. As a result we have a better understanding of their evolution during recognition and analytical formulas to compute them. We also show how this evolution can be projected onto the Stern-Brocot tree. These new relations have interesting consequences on the geometry of digital curves. We show how they can for instance be used to bound the slope difference between consecutive maximal segments

A review of hough transform and line segment detection approaches

In a wide range of image processing and computer vision problems, line segment detection is one of the most critical challenges. For more than three decades researchers have contributed to build more robust and accurate algorithms with faster performance. In this paper we review the main approaches and in particular the Hough transform and its extensions, which are among the most well-known techniques for the detection of straight lines in a digital image. This paper is based on extensive practical research and is organised into two main parts. In the first part, the HT and its major research directions and limitations are discussed. In the second part of the paper, state-of-the-art line segmentation techniques are reviewed and categorized into three main groups with fundamentally distinctive characteristics. Their relative advantages and disadvantages are compared and summarised in a table

A review of hough transform and line segment detection approaches

In a wide range of image processing and computer vision problems, line segment detection is one of the most critical challenges. For more than three decades researchers have contributed to build more robust and accurate algorithms with faster performance. In this paper we review the main approaches and in particular the Hough transform and its extensions, which are among the most well-known techniques for the detection of straight lines in a digital image. This paper is based on extensive practical research and is organised into two main parts. In the first part, the HT and its major research directions and limitations are discussed. In the second part of the paper, state-of-the-art line segmentation techniques are reviewed and categorized into three main groups with fundamentally distinctive characteristics. Their relative advantages and disadvantages are compared and summarised in a table

Tracking of secondary and temporary objects in structural concrete work

Previous research has shown that “Scan-vs-BIM ” object recognition systems, that fuse 3D point clouds from Terrestrial Laser Scanning (TLS) or digital photogrammetry with 4D project BIM, provide valuable information for tracking structural works. However, until now, the potential of these systems has been demonstrated for tracking progress of permanent structures only; no work has been reported yet on tracking secondary or temporary structures. For structural concrete work, temporary structures include formwork, scaffolding and shoring, while secondary components include rebar. Together, they constitute most of the earned value in concrete work. The impact of tracking such elements would thus be added veracity and detail to earned value calculations, and subsequently better project control and performance. This paper presents three different techniques for recognizing concrete construction secondary and temporary objects in TLS point clouds. Two of the techniques are tested using real-life data collected from a reinforced concrete building construction site. The preliminary experimental results show that it is feasible to recognize secondary and temporary objects in TLS point clouds with good accuracy; but it is envisaged that superior results could be achieved by using additional cues such colour and 3D edge information

ChemInk: A Natural Real-Time Recognition System for Chemical Drawings

We describe a new sketch recognition framework for chemical structure drawings that combines multiple levels of visual features using a jointly trained conditional random field. This joint model of appearance at different levels of detail makes our framework less sensitive to noise and drawing variations, improving accuracy and robustness. In addition, we present a novel learning-based approach to corner detection that achieves nearly perfect accuracy in our domain. The result is a recognizer that is better able to handle the wide range of drawing styles found in messy freehand sketches. Our system handles both graphics and text, producing a complete molecular structure as output. It works in real time, providing visual feedback about the recognition progress. On a dataset of chemical drawings our system achieved an accuracy rate of 97.4%, an improvement over the best reported results in literature. A preliminary user study also showed that participants were on average over twice as fast using our sketch-based system compared to ChemDraw, a popular CAD-based tool for authoring chemical diagrams. This was the case even though most of the users had years of experience using ChemDraw and little or no experience using Tablet PCs.National Science Foundation (U.S.) (Grant 0729422)United States. Dept. of Homeland Security (Graduate Research Fellowship)Pfizer Inc

Drip Paintings and Fractal Analysis

It has been claimed [1-6] that fractal analysis can be applied to unambiguously characterize works of art such as the drip paintings of Jackson Pollock. This academic issue has become of more general interest following the recent discovery of a cache of disputed Pollock paintings. We definitively demonstrate here, by analyzing paintings by Pollock and others, that fractal criteria provide no information about artistic authenticity. This work has also led to two new results in fractal analysis of more general scientific significance. First, the composite of two fractals is not generally scale invariant and exhibits complex multifractal scaling in the small distance asymptotic limit. Second the statistics of box-counting and related staircases provide a new way to characterize geometry and distinguish fractals from Euclidean objects

Improvements to the TCVD method to segment hand-drawn sketches

Tangent and Corner Vertices Detection (TCVD) is a method to detect corner vertices and tangent points in sketches using parametric cubic curves approximation, which is capable to detect corners with a high accuracy and a very low false positive rate, and also to detect tangent points far above other methods in literature. In this article, we present several improvements to TCVD method in order to establish mathematical conditions to detect corners and make the obtaining of curves independent from the scale, what increases the success ratio in transitions between lines and curves. The new conditions for obtaining corners use the radius as the inverse of the curvature, and the second derivative of the curvature. For the detection of curves, a new descriptor is presented, avoiding the parameters dependent of scale used in TCVD method. In order to obtain the performance of the implemented improvements, several tests have been carried out using a dataset which contains sketches more complex than those used for validation of TCVD algorithm (sketches with more curves and tangent points and sketches of different sizes). For corners detection, the accuracy obtained was pretty similar to that obtained with the previous TCVD, however, for curves and tangent points detection the accuracy increases significantly.Spanish Ministry of Science and Education and the FEDER Funds, through HYMAS project (Ref. DPI2010-19457) and INIA project VIS-DACSA (Ref. RTA2012-00062-C04-03) partially supported this work.Albert Gil, FE.; Aleixos Borrás, MN. (2017). Improvements to the TCVD method to segment hand-drawn sketches. Pattern Recognition. 63:416-426. https://doi.org/10.1016/j.patcog.2016.10.024S4164266

Moving Object Trajectories Meta-Model And Spatio-Temporal Queries

In this paper, a general moving object trajectories framework is put forward to allow independent applications processing trajectories data benefit from a high level of interoperability, information sharing as well as an efficient answer for a wide range of complex trajectory queries. Our proposed meta-model is based on ontology and event approach, incorporates existing presentations of trajectory and integrates new patterns like space-time path to describe activities in geographical space-time. We introduce recursive Region of Interest concepts and deal mobile objects trajectories with diverse spatio-temporal sampling protocols and different sensors available that traditional data model alone are incapable for this purpose.Comment: International Journal of Database Management Systems (IJDMS) Vol.4, No.2, April 201

An Empirical Study Comparing Unobtrusive Physiological Sensors for Stress Detection in Computer Work.

Several unobtrusive sensors have been tested in studies to capture physiological reactions to stress in workplace settings. Lab studies tend to focus on assessing sensors during a specific computer task, while in situ studies tend to offer a generalized view of sensors' efficacy for workplace stress monitoring, without discriminating different tasks. Given the variation in workplace computer activities, this study investigates the efficacy of unobtrusive sensors for stress measurement across a variety of tasks. We present a comparison of five physiological measurements obtained in a lab experiment, where participants completed six different computer tasks, while we measured their stress levels using a chest-band (ECG, respiration), a wristband (PPG and EDA), and an emerging thermal imaging method (perinasal perspiration). We found that thermal imaging can detect increased stress for most participants across all tasks, while wrist and chest sensors were less generalizable across tasks and participants. We summarize the costs and benefits of each sensor stream, and show how some computer use scenarios present usability and reliability challenges for stress monitoring with certain physiological sensors. We provide recommendations for researchers and system builders for measuring stress with physiological sensors during workplace computer use

Digital-Concrete Materials: Revisiting Fröbel in Sketchpad Tasks

The present paper sets out to revisit Fröbel’s play theory, through the open-ended instructional materials, designed for pupils’ learning which he bequeathed to us. Many researchers have highlighted the advantages of digital or computer concrete materials including DGS manipulatives for teaching and learning. In terms of the present study, it is interesting to mention the introduction of Fröbel’s first Gift that I adapted in the DGS environment, designed to provide a play-based way of presenting/inquiring about geometric objects. The proposed DGS materials can be displayed, inquired about, and managed through properly set-up tasks, using linking visual active representations. The dynamic notions (e.g., dynamic point, segment, instrumental decoding, hybrid-dynamic objects, etc.), are taken as given and form the specific theoretical basis for the required processes. Dynamic interdependencies of tools in various sequential steps will be considered for the idea of building DGS Gifts, linked to the pupils’ level of conceptualization