TY - GEN
T1 - 3D depth perception from single monocular images
AU - Xu, Hang
AU - Li, Kan
AU - Lv, Fu Yu
AU - Pei, Jian Meng
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Depth perception from single monocular images is a challenging problem in computer vision. Since the single image is lack of features of context, we only find all the cues from the local image. This paper presents a novel method for 3D depth perception from a single monocular image containing the ground to estimate the absolute depthmaps more accurately. Different from previous methods, in our method, we first generates the ground plane depth coordinate system from a single monocular image by image-forming principle, and then locates the objects in image with the coordinate system using the geometric characteristics. At last, we provide an method to estimate the accurate depthmaps. The experiments show that our method outperforms the state-of-the-art single-image depth perception methods both in relative depth perception and absolute depth perception.
AB - Depth perception from single monocular images is a challenging problem in computer vision. Since the single image is lack of features of context, we only find all the cues from the local image. This paper presents a novel method for 3D depth perception from a single monocular image containing the ground to estimate the absolute depthmaps more accurately. Different from previous methods, in our method, we first generates the ground plane depth coordinate system from a single monocular image by image-forming principle, and then locates the objects in image with the coordinate system using the geometric characteristics. At last, we provide an method to estimate the accurate depthmaps. The experiments show that our method outperforms the state-of-the-art single-image depth perception methods both in relative depth perception and absolute depth perception.
UR - http://www.scopus.com/inward/record.url?scp=84919683748&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-14445-0_44
DO - 10.1007/978-3-319-14445-0_44
M3 - Conference contribution
AN - SCOPUS:84919683748
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 510
EP - 521
BT - MultiMedia Modeling - 21st International Conference, MMM 2015, Proceedings
A2 - He, Xiangjian
A2 - Tao, Dacheng
A2 - Hasan, Muhammad Abul
A2 - Luo, Suhuai
A2 - Xu, Changsheng
A2 - Yang, Jie
PB - Springer Verlag
T2 - 21st International Conference on MultiMedia Modeling, MMM 2015
Y2 - 5 January 2015 through 7 January 2015
ER -