EZCam: WYSWYG Camera Manipulator for Path Design

EZCam: WYSWYG Camera Manipulator for Path Design [PDF] Cheng-Chi Li, Yu-Chi Lai, Nai-Sheng Hsu, Hong-Nan Kuo, Dobromir Todorov, Meng-Ting Tsai, Chih-Yuan Yao,

Abstract

With advance in movie industry, composite interactions and complex visual effects require to shoot at the designed part of a scene for immersion. Traditionally, the director of photography (DP) plans a camera path by recursively reviewing and commenting rendered results with it. Since the adjust-render-review process is not immediate and interactive, mis-communications happen to make the process ineffective and time consuming. Therefore, this work proposes a What-You-See-What-You-Get camera path reviewing system for the director to interactively instruct and design camera paths. Our system consists of a camera handle, a parameter control board, and a camera tracking box with mutually perpendicular marker planes. When manipulating the handle, the attached camera captures markers on visible planes with selected parameters to adjust the rendering view of the world. The director can directly examine results to give immediate comments and feedbacks for transformation and parameter adjustment in order to achieve effective communication and reduce the reviewing time. Finally, we conduct a set of qualitative and quantitative evaluations to show that our system is robust and efficient and can provide means to give interactive and immediate instructions for effective communication and efficiency enhancement during path design.

User Study

study 1: efficiency

technology	scene	average	stdev
MAYA	room	842.611	697.096
MAYA	racing	1102.444	540.794
MAYA	room+racing	972.528	628.841
EZCAM	room	81.111	58.422
EZCAM	racing	96.833	56.187
EZCAM	room+racing	88.972	57.051

3 factor ANOVA	Df	Sum Sq	Mean Sq	F value	Pr(>F)
tech	1	14052068	14052068	80.223	6.73E-13	***
scene	1	341689	341689	1.951	0.1673
order	1	631954	631954	3.608	0.062	.
tech:scene	1	224999	224999	1.285	0.2613
tech:order	1	228700	228700	1.306	0.2574
scene:order	1	603175	603175	3.444	0.0681	.
tech:scene:order	1	713433	713433	4.073	0.0478	*
Residuals	64	11210416	175163

2 factor ANOVA	Df	Sum Sq	Mean Sq	F value	Pr(>F)
tech	1	14052068	14052068	71.605	3.18E-12	***
scene	1	341689	341689	1.741	0.191
tech:scene	1	268156	268156	1.366	0.247
Residuals	68	13344519	196243

Download User Study 1 Result

study 2: operation times

technology	scene	avg time	stdev of time	avg op num	stdev of op nums
MAYA	room	1222.611	611.601	4.389	2.118
MAYA	racing	1106.722	410.144	3.389	1.614
MAYA	room+racing	1164.667	516.569	3.889	1.924
EZCAM	room	50.722	29.775	1.222	0.428
EZCAM	racing	62.722	29.017	1.556	0.616
EZCAM	room+racing	56.722	29.608	1.389	0.549

3 factor ANOVA for time	Df	Sum Sq	Mean Sq	F value	Pr(>F)
tech	1	22095736	22095736	181.797	<2e-16	***
scene	1	48568	48568	0.4	0.5295
order	1	282000	282000	2.32	0.1326
tech:scene	1	45630	45630	0.375	0.5422
tech:order	1	120743	120743	0.993	0.3227
scene:order	1	547170	547170	4.502	0.0377	*
tech:scene:order	1	547482	547482	4.505	0.0377	*
Residuals	64	7778621	121541

2 factor ANOVA for time	Df	Sum Sq	Mean Sq	F value	Pr(>F)
tech	1	22095736	22095736	162.468	<2e-16	***
scene	1	48568	48568	0.357	0.552
tech:scene	1	73600	73600	0.541	0.464
Residuals	68	9248047	136001

3 factor ANOVA for op num	Df	Sum Sq	Mean Sq	F value	Pr(>F)
tech	1	112.5	112.5	67.337	1.40E-11	***
scene	1	2	2	1.197	0.278
order	1	1.39	1.39	0.831	0.3653
tech:scene	1	8.87	8.87	5.308	0.0245	*
tech:order	1	5.26	5.26	3.146	0.0809	.
scene:order	1	6.81	6.81	4.074	0.0477	*
tech:scene:order	1	8.87	8.87	5.308	0.0245	*
Residuals	64	106.92	1.67

2 factor ANOVA for op num	Df	Sum Sq	Mean Sq	F value	Pr(>F)
tech	1	112.5	112.5	58.796	8.79E-11	***
scene	1	2	2	1.045	0.3102
tech:scene	1	8	8	4.181	0.0448	*
Residuals	68	130.1	1.91

Download User Study 2 Result