Conic Fitting Using the Geometric Distance

International audienceWe consider the problem of fitting a conic to a set of 2D points. It is commonly agreed that minimizing geometrical error, i.e. the sum of squared distances between the points and the conic, is better than using an algebraic error measure. However, most existing methods rely on algebraic error measures. This is usually motivated by the fact that point-to-conic distances are difficult to compute and the belief that non-linear optimization of conics is computationally very expensive. In this paper, we describe a parameterization for the conic fitting problem that allows to circumvent the difficulty of computing point-to-conic distances, and we show how to perform the non-linear optimization process efficiently

Interpretation of overtracing freehand sketching for geometric shapes

This paper presents a novel method for interpreting overtracing freehand sketch. The overtracing strokes are interpreted as sketch content and are used to generate 2D geometric primitives. The approach consists of four stages: stroke classification, strokes grouping and fitting, 2D tidy-up with endpoint clustering and parallelism correction, and in-context interpretation. Strokes are first classified into lines and curves by a linearity test. It is followed by an innovative strokes grouping process that handles lines and curves separately. The grouped strokes are fitted with 2D geometry and further tidied-up with endpoint clustering and parallelism correction. Finally, the in-context interpretation is applied to detect incorrect stroke interpretation based on geometry constraints and to suggest a most plausible correction based on the overall sketch context. The interpretation ensures sketched strokes to be interpreted into meaningful output. The interface overcomes the limitation where only a single line drawing can be sketched out as in most existing sketching programs, meanwhile is more intuitive to the user

Understanding fast macroscale fracture from microcrack post mortem patterns

Dynamic crack propagation drives catastrophic solid failures. In many amorphous brittle materials, sufficiently fast crack growth involves small-scale, high-frequency microcracking damage localized near the crack tip. The ultra-fast dynamics of microcrack nucleation, growth and coalescence is inaccessible experimentally and fast crack propagation was therefore studied only as a macroscale average. Here, we overcome this limitation in polymethylmethacrylate, the archetype of brittle amorphous materials: We reconstruct the complete spatio-temporal microcracking dynamics, with micrometer / nanosecond resolution, through post mortem analysis of the fracture surfaces. We find that all individual microcracks propagate at the same low, load-independent, velocity. Collectively, the main effect of microcracks is not to slow down fracture by increasing the energy required for crack propagation, as commonly believed, but on the contrary to boost the macroscale velocity through an acceleration factor selected on geometric grounds. Our results emphasize the key role of damage-related internal variables in the selection of macroscale fracture dynamics.Comment: 9 pages, 5 figures + supporting information (15 pages

A conceptual design tool: Sketch and fuzzy logic based system

A real time sketch and fuzzy logic based prototype system for conceptual design has been developed. This system comprises four phases. In the first one, the system accepts the input of on-line free-hand sketches, and segments them into meaningful parts by using fuzzy knowledge to detect corners and inflection points on the sketched curves. The fuzzy knowledge is applied to capture user’s drawing intention in terms of sketching position, direction, speed and acceleration. During the second phase, each segmented sub-part (curve) can be classified and identified as one of the following 2D primitives: straight lines, circles, circular arcs, ellipses, elliptical arcs or B-spline curves. Then, 2D topology information (connectivity, unitary constraints and pairwise constraints) is extracted dynamically from the identified 2D primitives. From the extracted information, a more accurate 2D geometry can be built up by a 2D geometric constraint solver. The 2D topology and geometry information is then employed to further interpretation of a 3D geometry. The system can not only accept sketched input, but also users’ interactive input of 2D and 3D primitives. This makes it friendly and easier to use, in comparison with ‘sketched input only’, or ‘interactive input only’ systems. Finally, examples are given to illustrate the system

Intelligent classification of sketch strokes

This paper presents an intelligent method for classifying pen strokes in an on-line sketching system. The method, based on adaptive threshold and fuzzy knowledge with respect to curve's linearity and convexity, can identify sketch strokes (curves) into lines, circles, arcs, ellipses, elliptical arcs, loop lines, spring lines and free-form B-spline curves. The proposed method has proven to be fast, suitable for real-time classification and identification

Relating vanishing points to catadioptric camera calibration

This paper presents the analysis and derivation of the geometric relation between vanishing points and camera parameters of central catadioptric camera systems. These vanishing points correspond to the three mutually orthogonal directions of 3D real world coordinate system (i.e. X, Y and Z axes). Compared to vanishing points (VPs) in the perspective projection, the advantages of VPs under central catadioptric projection are that there are normally two vanishing points for each set of parallel lines, since lines are projected to conics in the catadioptric image plane. Also, their vanishing points are usually located inside the image frame. We show that knowledge of the VPs corresponding to XYZ axes from a single image can lead to simple derivation of both intrinsic and extrinsic parameters of the central catadioptric system. This derived novel theory is demonstrated and tested on both synthetic and real data with respect to noise sensitivity