With　the　advancement　of　sensor　technology,　distributed　processing　technology,　and　wireless　communication,　Visual　Sensor　Networks　(VSNs)　are　widely　used.　However,　VSNs　also　have　flaws　such　as　poor　data　synchronization,　limited　node　resources,　and　complicated　node　management.　Thus,　this　paper　proposes　a　sensor　placement　optimization　method　to　save　network　resources　and　facilitate　management.　First,　some　necessary　models　are　established,　including　the　sensor　model,　the　space　model,　the　coverage　model,　and　the　reconstruction　error　model,　and　a　dimensionality　reduction　search　method　is　proposed.　Next,　following　the　creation　of　a　multi-objective　optimization　function　to　balance　reconstruction　error　and　coverage,　a　clever　optimization　algorithm　that　combines　the　benefits　of　Genetic　Algorithms　(GA)　and　Particle　Swarm　Optimization　(PSO)　is　applied.　Finally,　comparison　studies　validate　the　methodology　presented　in　this　paper,　and　the　combined　algorithm　can　enhance　optimization　effect　while　relatively　reducing　running　time.　In　addition,　a　sensor　coverage　method　for　large-range　target　space　with　obstacles　is　discussed.