scholarly journals Temporal Motion Vector Filter for Fast Object Detection on Compressed Video

2014 ◽  
Vol 29 (1) ◽  
pp. 12-24 ◽  
Author(s):  
R.C. Moura ◽  
E.M. Hemerly ◽  
A.M. Cunha
Keyword(s):  
Object Detection ◽  
Motion Vector ◽  
Compressed Video

An Improved Error Concealment Based on Redundant Motion Vector Information

2012 ◽  
Vol 532-533 ◽  
pp. 1219-1224
Author(s):  
Hong Tao Deng
Keyword(s):  
Video Transmission ◽  
Error Concealment ◽  
Video Quality ◽  
Motion Vector ◽  
Compressed Video ◽  
Vector Information ◽  
Vector Estimation ◽  
Channel Errors ◽  
Bit Stream

During video transmission over error prone network, compressed video bit-stream is sensitive to channel errors that may degrade the decoded pictures severely. In order to solve this problem, error concealment technique is a useful post-processing tool for recovering the lost information. In these methods, how to estimate the lost motion vector correctly is important for the quality of decoded picture. In order to recover the lost motion vector, an Decoder Motion Vector Estimation (DMVE) criterion was proposed and have well effect for recover the lost blocks. In this paper, we propose an improved error concealment method based on DMVE, which exploits the accurate motion vector by using redundant motion vector information. The experimental results with an H.264 codec show that our method improves both subjective and objective decoder reconstructed video quality, especially for sequences of drastic motion.

scholarly journals Moving Object Detection Using an Object Motion Reflection Model of Motion Vectors

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 34 ◽  
Author(s):  
Jisang Yoo ◽  
Gyu-cheol Lee
Keyword(s):  
Object Detection ◽  
Moving Objects ◽  
Probability Model ◽  
Motion Vector ◽  
Moving Object Detection ◽  
Object Motion ◽  
Moving Object ◽  
Disparity Map ◽  
Motion Vectors ◽  
Reflection Model

Moving object detection task can be solved by the background subtraction algorithm if the camera is fixed. However, because the background moves, detecting moving objects in a moving car is a difficult problem. There were attempts to detect moving objects using LiDAR or stereo cameras, but when the car moved, the detection rate decreased. We propose a moving object detection algorithm using an object motion reflection model of motion vectors. The proposed method first obtains the disparity map by searching the corresponding region between stereo images. Then, we estimate road by applying v-disparity method to the disparity map. The optical flow is used to acquire the motion vectors of symmetric pixels between adjacent frames where the road has been removed. We designed a probability model of how much the local motion is reflected in the motion vector to determine if the object is moving. We have experimented with the proposed method on two datasets, and confirmed that the proposed method detects moving objects with higher accuracy than other methods.

Motion vector composition algorithm for spatial scalability in compressed video

2001 ◽  
Vol 47 (3) ◽  
pp. 319-325 ◽  
Author(s):  
Mei-Juan Chen ◽  
Ming-Chung Chu ◽  
Shen-Yi Lo
Keyword(s):  
Motion Vector ◽  
Compressed Video
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