ObjectSense: A scalable multi-objects recognition system based on partial-duplicate image retrieval

ICMR 2013 - Proceedings of the 3rd ACM International Conference on Multimedia Retrieval

Volumn , Issue , 2013, Pages 317-318

  Wang, Shuang ^a   Xue, Yunfeng ^a   Chu, Lingyang ^a   Jiang, Yuhao ^b   Jiang, Shuqiang ^a  

^a INSTITUTE OF COMPUTING TECHNOLOGY   (China)

^b SHANDONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

accuracy; KNN; multi objects recognition; partial duplicate image retrieval; scalability

Indexed keywords

ACCURACY; IMAGE SIMILARITY; KNN; MULTI-OBJECTS; MULTIPLE OBJECTS; OBJECT CATEGORIES; OBJECT RECOGNITION SYSTEMS; RECOGNITION SYSTEMS;

IMAGE ANALYSIS; OBJECT RECOGNITION; SCALABILITY;

IMAGE RETRIEVAL;

EID: 84877596463     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2461466.2461524     Document Type: Conference Paper

References (3)

1. Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International journal of computer vision, 60(2), 91-110.
2. Nister, D., & Stewenius, H. (2006). Scalable recognition with a vocabulary tree. In Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on (Vol. 2, pp. 2161-2168). IEEE.
3. Sivic, J., & Zisserman, A. (2003, October). Video Google: A text retrieval approach to object matching in videos. In Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on (pp. 1470-1477). IEEE.