Video In Action

Discover the power of activism in this board book companion to New York Times bestsellers I Am Human and I Am Love One seed to start a garden, one note to start a melody, one brick to start breaking down walls: Every movement and moment of change starts with purpose, with intention, with one. With me. With you. From the #1 New York Times bestselling team behind I Am Yoga, I Am Peace, I Am Human, and I Am Love comes a powerful call to action, encouraging each reader to raise their voice, extend a hand, and take that one first step to start something beautiful and move toward a better world.

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This book introduces the use of video analysis into the popular educational research model of action research. Video analysis has become increasingly common in teacher development for reflective practice, as well as within the teacher certification process as an assessment tool. Kimberly Lebak builds on this use of video with a model that integrates the opportunities afforded by action research and video analysis for meaningful teacher development. Her "how-to" guide brings the theoretical and practical together to show teachers how video can be a concrete artifact for unpacking and reflecting on the complexities inherent in educational contexts. Chapter content helps readers bridge the gap between research and practice. Examples of tools that can be used for getting started with video-based action research are embedded in the chapters, including planning tools to help pinpoint opportunities for using video to identify a meaningful research topic and develop a data collection plan and action plan; and reflective tools for viewing the videos from multiple perspectives. Teacher vignettes further cement the applicability of the video-based action research model. This book is ideal for use by teachers at all stages of their careers, including pre-service teachers just embarking on their careers and in-service teachers looking to examine and improve their practices along with the learning of their students. It will have an additional benefit in teacher education programs as well as in undergraduate- or graduate-level action research courses by academic researchers and teacher educators.

Combining video analysis with the well-known Gradual Release of Responsibility (GRR) model, this book offers teacher educators a fresh perspective and a new tool for supporting teachers’ learning and reflection. The clearly articulated and useful framework shifts the focus away from children and toward teachers’ thinking about their own teaching practice. Interwoven with practical examples of the framework in use, this book identifies ways that teachers and teacher educators can foster more productive kinds of reflection about video-recorded classroom interactions and support preservice and inservice teachers. Offering key tools such as templates for reflection, video viewing guides, self-analysis checklists, and activities, this book moves the field forward and establishes video reflection and the GRR process as critical tools for teacher reflection, professional development, and effective teaching and learning.

Summary Elm is more than just a cutting-edge programming language, it’s a chance to upgrade the way you think about building web applications. Once you get comfortable with Elm’s refreshingly different approach to application development, you’ll be working with a clean syntax, dependable libraries, and a delightful compiler that essentially eliminates runtime exceptions. Elm compiles to JavaScript, so your code runs in any browser, and Elm’s best-in-class rendering speed will knock your socks off. Let’s get started! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Simply put, the Elm programming language transforms the way you think about frontend web development. Elm’s legendary compiler is an incredible assistant, giving you the precise and user-friendly support you need to work efficiently. Elm applications have small bundle sizes that run faster than JavaScript frameworks and are famously easy to maintain as they grow. The catch? Elm isn’t JavaScript, so you’ll have some new skills to learn. About the book Elm in Action teaches you the Elm language along with a new approach to coding frontend applications. Chapter by chapter, you’ll create a full-featured photo-browsing app, learning as you go about Elm’s modular architecture, Elm testing, and how to work seamlessly with your favorite JavaScript libraries. You’ll especially appreciate author and Elm core team member Richard Feldman’s unique insights, based on his thousands of hours writing production code in Elm. When you’re done, you’ll have a toolbox of new development skills and a stunning web app for your portfolio. What's inside Scalable design for production web applications Single-page applications in Elm Data modeling in Elm Accessing JavaScript from Elm About the reader For web developers with no prior experience in Elm or functional programming. About the author Richard Feldman is a software engineer at NoRedInk and a well-known member of the Elm community. Table of Contents PART 1 - GETTING STARTED 1. Welcome to Elm 2. Your first Elm application 3. Compiler as assistant PART 2 - PRODUCTION-GRADE ELM 4. Talking to servers 5. Talking to JavaScript 6. Testing PART 3 - BUILDING BIGGER 7. Data modeling 8. Single-page applications

With the vast development of Internet capacity and speed, as well as wide adop- tion of media technologies in people’s daily life, a large amount of videos have been surging, and need to be efficiently processed or organized based on interest. The human visual perception system could, without difficulty, interpret and r- ognize thousands of events in videos, despite high level of video object clutters, different types of scene context, variability of motion scales, appearance changes, occlusions and object interactions. For a computer vision system, it has been be very challenging to achieve automatic video event understanding for decades. Broadly speaking, those challenges include robust detection of events under - tion clutters, event interpretation under complex scenes, multi-level semantic event inference, putting events in context and multiple cameras, event inference from object interactions, etc. In recent years, steady progress has been made towards better models for video event categorisation and recognition, e. g. , from modelling events with bag of spatial temporal features to discovering event context, from detecting events using a single camera to inferring events through a distributed camera network, and from low-level event feature extraction and description to high-level semantic event classification and recognition. Nowadays, text based video retrieval is widely used by commercial search engines. However, it is still very difficult to retrieve or categorise a specific video segment based on their content in a real multimedia system or in surveillance applications.

The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.