Summary For The Test Sequences

Logitech Orbit 10ft Vertical Run 2

Frame 43: False detection due to glare Frame 141: Event of interest

Logitech Orbit 10ft Vertical Run 3

Frames 72&170: False detection due to dust

Frame 159: Event of interest

Logitech Orbit 20ft Vertical Run 2

Frame 150: Event of interest

Logitech Orbit 20ft Vertical Run 3

Frame 121: Event of interest

Logitech QuickCamPro 5000 10ft Vertical Run 3

Frame 150: Event of interest missed due to shadow and insufficient contrast

Frame 91: False detections due to dust

Logitech QuickCamPro 5000 20ft Vertical Run 2

No event of interest

Logitech QuickCamPro 5000 20ft Vertical Run 3

Frame 104: Event of interest

Challenges & Complexities• Motion versus change detection

– Aperture problem for optic flow approaches– Learning appropriate background for change (ghost objects appear due to

slow or fast learning)– Global camera motion/jitter

• Occlusion and Camouflage• Environmental problems

– Precipitation –rain, slow etc.– Wind –local object motion (swaying of branches, shadows) – Clutter (background model)– Dust and smoke

• Illumination problems– Shadows (static and moving cast shadow) - missed objects or false detections – Sudden illumination changes (cloud movements) – false detections– Glare – false detections, object shape and trajectory distortions– Low contrast or color saturation

Moving Object Detection Approaches1. Optical Flow Analysis: Characteristics of flow (velocity) vectors of moving

objects over time are used to detect changed regions. Advantage: can be used in the presence of camera motion.Disadvantage: usually computationally expensive & aperture problem.

2. Change Detectioni. Background subtraction: Moving regions are detected through

difference between the current frame and a reference background image.

| framei-Backgroundi |>ThAdvantage: provides the most complete feature data.Disadvantage: sensitive to dynamic scene changes due to lighting and

extraneous events and cannot handle global motion.ii. Temporal differencing: Similar to background subtraction but the

estimated background is the previous frame. | framei-framei-1 |>Th

Advantage: very adaptive to dynamic environments.Disadvantage: has problems in extraction of all relevant feature pixels

(aperture problem).