Glyph-Based Video Visualization for Semen Analysis

Abstract

The existing efforts in computer assisted semen analysis have been focused on high speed imaging and automated image analysis of sperm motility. This results in a large amount of data, and it is extremely challenging for both clinical scientists and researchers to interpret, compare and correlate the multidimensional and time-varying measurements captured from video data. In this work, we use glyphs to encode a collection of numerical measurements taken at a regular interval and to summarize spatio-temporal motion characteristics using static visual representations. The design of the glyphs addresses the needs for (a) encoding some 20 variables using separable visual channels, (b) supporting scientific observation of the interrelationships between different measurements and comparison between different sperm cells and their flagella, and (c) facilitating the learning of the encoding scheme by making use of appropriate visual abstractions and metaphors. As a case study, we focus this work on video visualization for computer-aided semen analysis, which has a broad impact on both biological sciences and medical healthcare. We demonstrate that glyph-based visualization can serve as a means of external memorization of video data as well as an overview of a large set of spatiotemporal measurements. It enables domain scientists to make scientific observation in a cost-effective manner by reducing the burden of viewing videos repeatedly, while providing them with a new visual representation for conveying semen statistics.

Glyph-based video visualization on Google Map for surveillance in smart cities

“…Glyph-based visualization is considered to be a common form of visual design in which collection of visual objects are used to represent data set [9]. Glyph technique is used to visualize motion vectors which are overlaid on every frame of the video stream in this approach.…”

“…The visualization of videos is gaining more attention [2,3] because of addressing challenges of data analysis arisen from video cameras contents [4][5][6]. Over the past decade, VV usefulness for traffic surveillance [7,8] application has been effectively demonstrated by researchers [9,10].…”

“…VV offers Spatio-temporal summary and overview of large collection of videos, and its abstract representation of meaningful information assists the users in video content [9,11]. Conversely, conventional techniques of visual representation such as time series plot have difficulties in conveying impressions from large video collection [9].…”

“…Conversely, conventional techniques of visual representation such as time series plot have difficulties in conveying impressions from large video collection [9].…”

Visual analytics for video applications

“…Recently, a wide range of applications and challenges in the areas of medicine, sports and science have arisen. An example of VA in medicine is a tool for interpreting and comparing sperm motility measurements captured from video [2], which employs a glyph-based visualization. Several applications in science can be found by the works of Romero and colleagues [23,25].…”