Browsing by Author "Chien, Chun-Liang"

Now showing 1 - 6 of 6

An Image Based Overexposed Taillight Detection Method for Frontal Vehicle Detection in Night Vision
(2016)
Chien, Chun-Liang
;
Hang, Hsueh-Ming
;
Tseng, Din-Chang
;
Chen, Yong-Sheng
;
交大名義發表
To achieve the goal of frontal vehicle detection in night-driving condition, we propose an effective method to detect the red taillights of vehicles. The challenge is that the taillight images captured with automatic exposure typically are overexposed, which makes red color segmentation often erroneous. Instead of customizing the camera hardware to tackle this problem, we combine morphological and logical operations to extract the overexposed region in taillights, which leads to a much more reliable taillight detection scheme. Then, we develop a robust pairing process that clusters two taillight candidates into a pair that represents a vehicle. Several criteria are considered in the pairing process, including the similarities of area, shape, and height of a pair of lights. In addition, we include the temporal consistency criterion; that is, a pair of taillights should be continually detected for a certain duration of time. An energy function is used to aggregate these criteria together. Our experiments show that both the missing and false detection rates are lower than 1.5%.
Image Fusion With No Gamut Problem by Improved Nonlinear IHS Transforms for Remote Sensing
(2014-01-01)
Chien, Chun-Liang
;
Tsai, Wen-Hsiang
;
資訊工程學系
;
Department of Computer Science
An image fusion method must ideally preserve both the detail of the panchromatic image and the color of the multispectral image. Existing image fusion methods incur the gamut problem of creating new colors which fall out of the RGB cube. These methods solve the problem by color clipping which yields undesirable color distortions and contrast reductions. An improved nonlinear IHS (intensity, hue, saturation; iNIHS) color space and related color transformations are proposed in this paper to solve the gamut problem without appealing to color clipping. The iNIHS space includes two halves, one being constructed from the lower half of the RGB cube by RGB to IHS transformations, and the other from the upper half of the RGB cube by CMY to IHS transformations. While incurring no out-of-gamut colors, desired intensity substitutions and additions in substitutive and additive image fusions, respectively, are all achievable, with the saturation component regulated within the maximum attainable range. Good experimental results show the feasibility of the proposed method.
Intra Block Copy Hash Reduction for HEVC Screen Content Coding
(2016)
Kuo, Che-Wei
;
Hang, Hsueh-Ming
;
Chien, Chun-Liang
;
交大名義發表
;
National Chiao Tung University
To meet a wide range of needs for video applications such as remote desktop, video conference, distance education, and cloud gaming, the ISO/ITU Joint Collaborative Team on Video Coding (JCT-VC) committee is recently specifying the Screen Content Coding (SCC) standard, as one of the extensions of High Efficiency Video Coding (HEVC). In this paper, the hash search method of the standard adopted Intra Block Copy (IBC) coding tool for SCC is investigated. We collect the coded data using the current hash table and examine their efficiency and explore possible ways for further improvement. A low complexity scheme of selecting effective hash nodes and a modified hash key generation method are presented. Experimental results show that the proposed method reduces on the average 37% or at most 70% hash table memory usage but it preserves the similar BD-rate savings and encoding complexity when integrated into the SCM-3.0 test model.
View Synthesis for 3D Video Scene Composition
(2015)
Wang, Amanda
;
Chien, Chun-Liang
;
Hang, Hsueh-Ming
;
電機學院
;
電子工程學系及電子研究所
Scene composition is a method widely used in movie and TV production. Merging two sets of 3D videos into one is a very challenging task. There are several main issues on video composition. Our focus is compositing two sets of videos with different camera motion parameters. The key techniques are the camera motion estimation and view synthesis technique used to produce the synthesized motion-compensated background video. We propose a refined backward warping technique for view synthesis and adopt the ICP algorithm to calculate the camera motion parameters.
VIRTUAL VIEW SYNTHESIS QUALITY REFINEMENT
(2016)
Lee, Tzu-Chin
;
Chien, Chun-Liang
;
Hang, Hsueh-Ming
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
A 3D virtual view synthesis system is to generate a virtual view at an arbitrary viewpoint from the texture and depth information of multiple reference views. There are several technical challenges in producing a high-quality synthesized view such as warping, blending, ghost artifact reduction and hole filling. Four tools ( techniques) have been proposed in this paper to solve these problems. They are unreliable region extraction, fast backward warping, adaptive blending, and hole filling by using the constructed background models. Other techniques such as disocclusion detection, bicubic interpolation, and background model construction are also employed in the proposed algorithm. All above techniques have been designed and tested on the MPEG test sequences. Experimental results show that high-quality virtual views are generated with fewer artifacts.
VIRTUAL VIEW SYNTHESIS USING RGB-D CAMERAS
(2016)
Chien, Chun-Liang
;
Lee, Tzu-Chin
;
Hang, Hsueh-Ming
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
A view synthesis problem is to generate a virtual view based on the given one or multiple views and their associated depth maps. We adopt the depth image based rendering (DIBR) approach in this paper for synthesizing the new views. No explicit 3D modeling is involved. Another component of this study is the popular commodity RGB-D (color plus depth) cameras. The color and depth images captured by a pair of RGB-D cameras (Microsoft Kinect for Windows v2) are our inputs to synthesize intermediate virtual views between these two cameras. Several methods include depth to color warping, disocclusion filling, and color to color warping are adopted and designed to achieve this target. One of our major contributions is a new disocclusion detection algorithm proposed to improve the disocclusion filling result. Furthermore, an improved camera calibration method is proposed to make use of the additional depth information. Good quality synthesized views are shown at the end.