A complexity-level analysis of the sensor planning task for object search

Computational Intelligence

Volumn 17, Issue 4, 2001, Pages 605-620

  Ye, Yiming ^a   Tsotsos, John K ^b  

^a IBM T J WATSON RESEARCH CENTER   (United States)

^b YORK UNIVERSITY   (Canada)

Author keywords

Complexity; Computer vision; Object search; Robotics; Sensor planning

Indexed keywords

CAMERAS; COMPUTATIONAL COMPLEXITY; COMPUTER VISION; IMAGE ANALYSIS; IMAGE SENSORS; ROBOTICS;

SENSOR PLANNING;

OBJECT RECOGNITION;

EID: 0035510142     PISSN: 08247935     EISSN: None     Source Type: Journal    
DOI: 10.1111/0824-7935.00166     Document Type: Article

References (15)

1. Active perception vs. passive perception
2. The combinatorics of local constraints in model-based recognition and localization from sparse data
3. The complexity of recognizing polyhedral scenes
4. How to decide from the first view where to look next
5. An algorithm for constructing the aspect graph
6. Analyzing vision at the complexity level
7. Active versus passive perception, which is more efficient?
8. Using intermediate objects to improve the efficiency of Visual search
9. Where to look next in 3d object search
10. Sensor planning in 3d object search: Its formulation and complexity
11. Knowledge difference and its influence on a search agent