Semi-Automated SVG Programming via Direct Manipulation

Direct manipulation interfaces provide intuitive and interactive features to a broad range of users, but they often exhibit two limitations: the built-in features cannot possibly cover all use cases, and the internal representation of the content is not readily exposed. We believe that if direct manipulation interfaces were to (a) use general-purpose programs as the representation format, and (b) expose those programs to the user, then experts could customize these systems in powerful new ways and non-experts could enjoy some of the benefits of programmable systems. In recent work, we presented a prototype SVG editor called Sketch-n-Sketch that offered a step towards this vision. In that system, the user wrote a program in a general-purpose lambda-calculus to generate a graphic design and could then directly manipulate the output to indirectly change design parameters (i.e. constant literals) in the program in real-time during the manipulation. Unfortunately, the burden of programming the desired relationships rested entirely on the user. In this paper, we design and implement new features for Sketch-n-Sketch that assist in the programming process itself. Like typical direct manipulation systems, our extended Sketch-n-Sketch now provides GUI-based tools for drawing shapes, relating shapes to each other, and grouping shapes together. Unlike typical systems, however, each tool carries out the user's intention by transforming their general-purpose program. This novel, semi-automated programming workflow allows the user to rapidly create high-level, reusable abstractions in the program while at the same time retaining direct manipulation capabilities. In future work, our approach may be extended with more graphic design features or realized for other application domains.Comment: In 29th ACM User Interface Software and Technology Symposium (UIST 2016

Stochastic Dynamics for Video Infilling

In this paper, we introduce a stochastic dynamics video infilling (SDVI) framework to generate frames between long intervals in a video. Our task differs from video interpolation which aims to produce transitional frames for a short interval between every two frames and increase the temporal resolution. Our task, namely video infilling, however, aims to infill long intervals with plausible frame sequences. Our framework models the infilling as a constrained stochastic generation process and sequentially samples dynamics from the inferred distribution. SDVI consists of two parts: (1) a bi-directional constraint propagation module to guarantee the spatial-temporal coherence among frames, (2) a stochastic sampling process to generate dynamics from the inferred distributions. Experimental results show that SDVI can generate clear frame sequences with varying contents. Moreover, motions in the generated sequence are realistic and able to transfer smoothly from the given start frame to the terminal frame. Our project site is https://xharlie.github.io/projects/project_sites/SDVI/video_results.htmlComment: Winter Conference on Applications of Computer Vision (WACV 2020

Programmatic and Direct Manipulation, Together at Last

Direct manipulation interfaces and programmatic systems have distinct and complementary strengths. The former provide intuitive, immediate visual feedback and enable rapid prototyping, whereas the latter enable complex, reusable abstractions. Unfortunately, existing systems typically force users into just one of these two interaction modes. We present a system called Sketch-n-Sketch that integrates programmatic and direct manipulation for the particular domain of Scalable Vector Graphics (SVG). In Sketch-n-Sketch, the user writes a program to generate an output SVG canvas. Then the user may directly manipulate the canvas while the system immediately infers a program update in order to match the changes to the output, a workflow we call live synchronization. To achieve this, we propose (i) a technique called trace-based program synthesis that takes program execution history into account in order to constrain the search space and (ii) heuristics for dealing with ambiguities. Based on our experience with examples spanning 2,000 lines of code and from the results of a preliminary user study, we believe that Sketch-n-Sketch provides a novel workflow that can augment traditional programming systems. Our approach may serve as the basis for live synchronization in other application domains, as well as a starting point for yet more ambitious ways of combining programmatic and direct manipulation.Comment: PLDI 2016 Paper + Supplementary Appendice

Inferring Termination Conditions for Logic Programs using Backwards Analysis

This paper focuses on the inference of modes for which a logic program is guaranteed to terminate. This generalises traditional termination analysis where an analyser tries to verify termination for a specified mode. Our contribution is a methodology in which components of traditional termination analysis are combined with backwards analysis to obtain an analyser for termination inference. We identify a condition on the components of the analyser which guarantees that termination inference will infer all modes which can be checked to terminate. The application of this methodology to enhance a traditional termination analyser to perform also termination inference is demonstrated

A new model to predict weak-lensing peak counts II. Parameter constraint strategies

Peak counts have been shown to be an excellent tool to extract the non-Gaussian part of the weak lensing signal. Recently, we developped a fast stochastic forward model to predict weak-lensing peak counts. Our model is able to reconstruct the underlying distribution of observables for analyses. In this work, we explore and compare various strategies for constraining parameter using our model, focusing on the matter density $\Omega_\mathrm{m}$ and the density fluctuation amplitude $\sigma_8$. First, we examine the impact from the cosmological dependency of covariances (CDC). Second, we perform the analysis with the copula likelihood, a technique which makes a weaker assumption compared to the Gaussian likelihood. Third, direct, non-analytic parameter estimations are applied using the full information of the distribution. Fourth, we obtain constraints with approximate Bayesian computation (ABC), an efficient, robust, and likelihood-free algorithm based on accept-reject sampling. We find that neglecting the CDC effect enlarges parameter contours by 22%, and that the covariance-varying copula likelihood is a very good approximation to the true likelihood. The direct techniques work well in spite of noisier contours. Concerning ABC, the iterative process converges quickly to a posterior distribution that is in an excellent agreement with results from our other analyses. The time cost for ABC is reduced by two orders of magnitude. The stochastic nature of our weak-lensing peak count model allows us to use various techniques that approach the true underlying probability distribution of observables, without making simplifying assumptions. Our work can be generalized to other observables where forward simulations provide samples of the underlying distribution.Comment: 15 pages, 11 figures. Accepted versio