Abstract
In this paper, we propose a method to recognize the 6DoF pose of multiple objects simultaneously. One good solution to recognize them is applying a Hypothesis Verification (HV) algorithm. This type of algorithm evaluates consistency between an input scene and scene hypotheses represented by combinations of object candidates generated from the model based matching. Its use achieves reliable recognition because it maximizes the fitting score between the input scene and the scene hypotheses instead of maximizing the fitting score of an object candidate. We have developed a more reliable HV algorithm that uses a novel cue, the naturalness of an object’s layout (its physical reasoning). This cue evaluates whether the object’s layout in a scene hypothesis can actually be achieved by using simple collision detection. Experimental results show that using the physical reasoning have improved recognition reliability.
| Original language | English |
|---|---|
| Title of host publication | Computer Vision – ECCV 2016 Workshops, Proceedings |
| Publisher | Springer Verlag |
| Pages | 595-605 |
| Number of pages | 11 |
| Volume | 9915 LNCS |
| ISBN (Print) | 9783319494081 |
| DOIs | |
| Publication status | Published - 2016 |
| Externally published | Yes |
| Event | 14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands Duration: 2016 Oct 8 → 2016 Oct 16 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 9915 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 14th European Conference on Computer Vision, ECCV 2016 |
|---|---|
| Country | Netherlands |
| City | Amsterdam |
| Period | 16/10/8 → 16/10/16 |
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Keywords
- 3D object recognition
- Collision detection
- Hypothesis verification
- Point cloud
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Physical reasoning for 3D object recognition using global hypothesis verification. / Akizuki, Shuichi; Hashimoto, Manabu.
Computer Vision – ECCV 2016 Workshops, Proceedings. Vol. 9915 LNCS Springer Verlag, 2016. p. 595-605 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9915 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Physical reasoning for 3D object recognition using global hypothesis verification
AU - Akizuki, Shuichi
AU - Hashimoto, Manabu
PY - 2016
Y1 - 2016
N2 - In this paper, we propose a method to recognize the 6DoF pose of multiple objects simultaneously. One good solution to recognize them is applying a Hypothesis Verification (HV) algorithm. This type of algorithm evaluates consistency between an input scene and scene hypotheses represented by combinations of object candidates generated from the model based matching. Its use achieves reliable recognition because it maximizes the fitting score between the input scene and the scene hypotheses instead of maximizing the fitting score of an object candidate. We have developed a more reliable HV algorithm that uses a novel cue, the naturalness of an object’s layout (its physical reasoning). This cue evaluates whether the object’s layout in a scene hypothesis can actually be achieved by using simple collision detection. Experimental results show that using the physical reasoning have improved recognition reliability.
AB - In this paper, we propose a method to recognize the 6DoF pose of multiple objects simultaneously. One good solution to recognize them is applying a Hypothesis Verification (HV) algorithm. This type of algorithm evaluates consistency between an input scene and scene hypotheses represented by combinations of object candidates generated from the model based matching. Its use achieves reliable recognition because it maximizes the fitting score between the input scene and the scene hypotheses instead of maximizing the fitting score of an object candidate. We have developed a more reliable HV algorithm that uses a novel cue, the naturalness of an object’s layout (its physical reasoning). This cue evaluates whether the object’s layout in a scene hypothesis can actually be achieved by using simple collision detection. Experimental results show that using the physical reasoning have improved recognition reliability.
KW - 3D object recognition
KW - Collision detection
KW - Hypothesis verification
KW - Point cloud
UR - http://www.scopus.com/inward/record.url?scp=85006062524&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85006062524&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-49409-8_51
DO - 10.1007/978-3-319-49409-8_51
M3 - Conference contribution
AN - SCOPUS:85006062524
SN - 9783319494081
VL - 9915 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 595
EP - 605
BT - Computer Vision – ECCV 2016 Workshops, Proceedings
PB - Springer Verlag
ER -