CIVR 2009 - PDF Preprint Papers

CIVR 2009 Conference On Image And Video Retrieval

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CIVR
2009
Springer

583views Image Analysis» more CIVR 2009»

Mining from Large Image Sets

15 years 15 days ago

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So far, most image mining was based on interactive querying. Although such querying will remain important in the future, several applications need image mining at such wide scale...

Luc J. Van Gool, Michael D. Breitenstein, Stephan ...

posted by bremicha

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Id	Views	Title	Status

1	583	Mining from Large Image Sets
2	315	Exploiting Facial Expressions for Affective Video Summarisation
3	257	Trajectory-based handball video understanding	claim
4	253	Spatial extensions to bag of visual words	claim
5	229	A human-machine collaborative approach to tracking human movement in multi-camera video	claim
6	221	Movie segmentation into scenes and chapters using locally weighted bag of visual words	claim
7	212	NUS-WIDE: a real-world web image database from National University of Singapore	claim
8	212	Video copy detection by fast sequence matching	claim
9	192	Example based video filters	claim
10	174	Evaluation of GIST descriptors for web-scale image search	claim
11	169	Exploiting contextual data for event retrieval in surveillance video	claim
12	151	Reusing annotation labor for concept selection	claim
13	149	Global annotation on georeferenced photographs	claim
14	147	Integrating visual and semantic contexts for topic network generation and word sense disambiguation	claim
15	146	Web news categorization using a cross-media document graph	claim
16	145	Jointly optimising relevance and diversity in image retrieval	claim
17	141	Automatic retrieval of visual continuity errors in movies	claim
18	138	Context-based multi-label image annotation	claim
19	137	Multilayer pLSA for multimodal image retrieval	claim
20	134	Towards surveillance video search by natural language query	claim
21	133	MonuAnno: automatic annotation of georeferenced landmarks images	claim
22	132	Real-time bag of words, approximately	claim
23	131	Supporting aspect-based video browsing: analysis of a user study	claim
24	130	Exploring inter-concept relationship with context space for semantic video indexing	claim
25	123	Image annotation using clickthrough data	claim
26	121	A procedure of adaptive kernel combination with kernel-target alignment for object classification	claim
27	119	User variance and its impact on video retrieval benchmarking	claim
28	112	Dense sampling and fast encoding for 3D model retrieval using bag-of-visual features	claim
29	108	High-entropy layouts for content-based browsing and retrieval	claim
30	95	Human computation	claim

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